Whether you’ve already gotten your data science degree or you’re considering a job in the field of data science, you may be wondering, how does a data science degree translate into a real-world job? What kind of positions should you be considering? 

It’s easy to feel lost when you consider the massive number of possibilities that a data science degree opens up. Do you concentrate on statistics or coding or something in between? Not to worry, your data science degree opens the doors to some of the most exciting and well-paid jobs in the industry.

Here are the top 15 data science degree jobs you should consider. 

  • Data Scientist
  • Data Analyst
  • Data Engineer
  • Machine Learning Engineer
  • Business Intelligence Analyst
  • Quantitative Analyst
  • Data Architect
  • Statistician
  • Big Data Engineer/Architect
  • Data Visualization Specialist
  • Data and Analytics Manager
  • Bioinformatician
  • Database Administrator
  • Predictive Modeler
  • Geospatial Professional

1. Data Scientist

The role of a Data Scientist is one of the most coveted positions in the field of data science. Data Scientists are analytical experts who use their skills in both technology and social science to find trends, manage data, and uncover solutions to business challenges.

As a Data Scientist

Your responsibilities may include designing and implementing models and algorithms, interpreting and analyzing complex data sets to drive business strategies and decisions. You may also develop custom data models and algorithms, work with different stakeholders to identify opportunities for leveraging company data, and use predictive modeling to enhance customer experiences, revenue generation, and other business outcomes.


  • High Demand in Various Industries: Data scientists are sought after in a wide array of sectors, from healthcare to finance to e-commerce. Their skills in data analysis, prediction, and insights generation are valuable to organizations looking to leverage vast amounts of data for decision-making, making data scientist roles both prevalent and diverse.
  • Generous Compensation: Due to the specialized skill set required and the significant impact they can have on business outcomes, data scientists are often offered competitive salaries and benefits. This reflects both the scarcity of their expertise and the value they provide to employers.
  • Continuous Learning and Growth: The field of data science is ever-evolving, with new tools, algorithms, and technologies emerging regularly. This dynamic nature of the field offers data scientists opportunities to continually update their knowledge, ensuring that their work remains both challenging and rewarding.
  • Interdisciplinary Collaboration: Data scientists often collaborate with experts from other fields, such as marketing, finance, or engineering. This fosters a holistic approach to problem-solving, allowing for comprehensive solutions and the integration of varied perspectives, enriching the professional experience.
  • Potential to Drive Significant Impact: Data scientists have the power to derive actionable insights from raw data, which can lead to transformative changes in a company. Whether it’s optimizing operations, enhancing customer experiences, or predicting market trends, the insights provided by data scientists can be pivotal for business success.

Working Conditions

The working conditions of a data scientist vary depending on the industry, company size, and specific role, but there are some commonalities. While the job is intellectually stimulating, it can also be demanding and may occasionally require long hours to meet project deadlines.The environment tends to prioritize continuous learning, given the rapid advancements in technology and methods, leading many data scientists to allocate time for upskilling and research.

Many enjoy the flexibility of remote work, especially post-pandemic, with companies embracing digital transformation. The job is primarily computer-based, requiring long hours in front of screens. This means a significant portion of the day might be spent coding, analyzing data, or attending virtual meetings.

Further Studies

  • Ph.D. can be beneficial for more advanced roles.

What Skills Make You a Strong Candidate

You are highly analytical and possess a strong background in data analysis, statistics, and machine learning. You have an innate curiosity, a problem-solving mindset, and are skilled at interpreting complex information. Additionally, you demonstrate excellent communication skills to effectively present your findings to both technical and non-technical colleagues.

Salary Range & Job Outlook

Average Salary ($125,242)
Job Outlook (36%)

The average data scientist’s salary in the US is $125,242 per year. Employment of data scientists is projected to grow 36% from 2021 to 2031, much faster than the average for all occupations.

2. Data Analysts

Data Analysts are essential figures in understanding and utilizing company data. They transform large sets of raw data into actionable insights that help inform strategic decisions. Their role is vital in today’s data-driven world, as they assist organizations in making sense of the data collected and provide meaningful interpretations.

As a Data Analyst

You typically gather data from various sources, clean and validate data for accuracy, analyze and interpret results using statistical techniques, and provide ongoing reports. You develop and implement data analyses, data collection systems, and other strategies that optimize statistical efficiency and quality. Additionally, you identify patterns and trends in data sets and work alongside teams to establish business needs.


  • Wide Range of Employment Opportunities: Data analysts are in demand across numerous sectors, including finance, healthcare, marketing, and technology. Their expertise in interpreting data ensures that they are valuable assets in any organization aiming to make data-driven decisions, leading to ample job openings in diverse industries.
  • Skill Transferability: The core skills acquired as a data analyst, such as data wrangling, statistical analysis, and reporting, are transferable to many other roles and sectors. This flexibility allows data analysts to pivot or transition into various areas based on interest or market demand.
  • Professional Development and Learning: The dynamic nature of data analytics ensures that there’s always something new to learn. From new software tools to advanced statistical techniques, data analysts continually have opportunities to expand their knowledge and hone their expertise, making the role consistently engaging.
  • Direct Impact on Decision Making: Data analysts play a pivotal role in shaping organizational strategies by providing actionable insights from data. This central position allows them to witness firsthand the effects of their analysis on business outcomes, giving a sense of accomplishment and influence within the company.
  • Collaborative Work Environment: Data analysts often work in teams and collaborate with various departments, from marketing to finance to operations. This collaborative setting promotes a multidisciplinary approach to problems and enriches the work experience by fostering diverse viewpoints and teamwork.

Working Conditions

Working as a data analyst typically involves a structured office environment, whether in a physical office space or virtually from home, especially in the aftermath of the global shift towards remote work. The nature of the job is predominantly computer-centric, which means analysts spend a substantial amount of their time utilizing analytical software, databases, and spreadsheet tools on their workstations. 

Given the precision required in data handling, it’s not uncommon for analysts to dedicate prolonged hours scrutinizing datasets, generating reports, or crafting visualizations to clearly convey their findings. The role also demands constant collaboration, so frequent meetings with various stakeholders, such as business managers, IT teams, or other data professionals, are part and parcel of the job.

Further Studies

  • A Master’s Degree in data science may be beneficial for advanced positions.

What Skills Make You a Strong Candidate

You are a detail-oriented, logical thinkers with a passion for problem-solving. You have a solid understanding of data collection, manipulation, and analysis techniques. You also possess excellent communication skills, allowing you to explain complex concepts in simple terms and present findings effectively to stakeholders.

Salary Range & Job Outlook

Average Salary ($69,000)
Job Outlook (12%)

Market Research Analysts, Operations Research Analyst, and Management Analysts are all ranked in the top 20. The Global Big Data Analytics Market is expected to be worth $105 billion by 2027, which reflects a more than 12% growth from 2019 to 2027.. As of December 2021, the median pay in the U.S. for a Data Analyst was $69,000, according to Glassdoor.

3. Data Engineer

Data Engineers are pivotal in the successful operation of businesses in a data-driven environment. They are the architects who build and maintain the systems that allow data to be used effectively. Their role involves a lot more than just working with large volumes of data; they’re responsible for designing, creating, and maintaining the data processing system and infrastructure.

As a Data Engineer

You’ll design, construct, install, test, and maintain highly scalable data management systems. You ensure that systems meet business requirements and industry practices. You are also responsible for integrating new data management technologies and software engineering tools into existing structures, as well as developing set processes for data mining, data modeling, and data production.


  • Foundation of Data-driven Decisions: Data engineers lay the groundwork for organizations to harness the power of data analytics and machine learning. Their efforts in designing and maintaining robust data architectures enable businesses to make informed choices, placing them at the heart of the modern data ecosystem.
  • Highly Competitive Compensation: Given the technical expertise and specialization required for the role, data engineers often command attractive salaries and benefits. Their unique skill set, combined with the increasing reliance of companies on data, results in a favorable compensation landscape for these professionals.
  • Dynamic and Evolving Field: The realm of data engineering is continuously evolving with technological advancements and emerging tools. This dynamic environment ensures that data engineers always have opportunities for learning, innovation, and exploration of new platforms and methodologies.
  • Clear Path to Career Advancement: As companies invest heavily in their data infrastructure, experienced data engineers often find opportunities to progress into senior roles, such as lead engineer, data architect, or even managerial positions overseeing entire data teams.
  • Interdisciplinary Collaborations: Data engineers often collaborate with other professionals like data scientists, analysts, and business leaders. These interactions provide a holistic view of the organization’s data needs and challenges, allowing data engineers to design solutions that cater to a broader range of requirements and fostering a more inclusive and enriching work experience.

Working Conditions

Data engineers primarily operate within a technical and digital workspace, often situated in modern office environments or, increasingly, within remote or hybrid work settings. Their day-to-day tasks demand deep immersion in complex data systems, platforms, and coding, necessitating a setup equipped with powerful computers and multiple monitors for efficient multitasking. 

The nature of their job—designing, constructing, installing, and maintaining large-scale processing systems—means they are frequently engaged in problem-solving, often navigating challenges that require innovative solutions. This can sometimes lead to extended hours, especially when dealing with system outages or urgent data infrastructure updates. Collaboration is integral to their role; data engineers routinely liaise with data scientists, analysts, and other IT professionals to ensure data pipelines are robust and optimized for analysis.

Further Studies

  • Certifications in big data technologies such as Hadoop or Spark can be beneficial.
  • Knowledge of database systems, both SQL and NoSQL, and programming languages such as Python or Java.

What Skills Make You a Strong Candidate

To become a successful Data Engineer, you should have strong problem-solving skills as well as a high degree of technical knowledge including software development, data architectures, and data warehousing. You also need a deep understanding of databases and best engineering practices, including data modeling, ETL (Extract, Transform, Load) operations, and agile development. Good communication skills are also important as you’ll often need to explain their work to colleagues who don’t have a technical background.

Salary Range & Job Outlook

Average Salary ($109,675)
Job Outlook (21%)

Projected job growth for data engineers is 21% from 2018-2028 owing to the surge in artificial intelligence, machine learning and natural language processing technology. The average salary for a data engineer is $109,675.

degree guide data science

4. Statistician

A Statistician is a mathematical expert who uses statistical theories and methods to collect, analyze, and interpret quantitative data and trends. Statisticians may work in a range of sectors, such as health, education, marketing, sports, or government, providing valuable insights to influence policy or decision-making.

As a Statistician

You’ll design surveys, questionnaires, experiments, or opinion polls to collect data. You’ll process and analyze that data to draw conclusions or make predictions. You’ll also use statistical software to manage and organize information, apply statistical theories to solve complex problems and report their findings using charts, graphs, or reports.


  • Broad Application Across Sectors: Statisticians have the unique advantage of being relevant in a myriad of industries, from healthcare and government to finance and sports. Their expertise in data interpretation and hypothesis testing allows them to contribute meaningfully to various fields, making their skill set universally valued.
  • Opportunities for Groundbreaking Research: Many statisticians are at the forefront of significant research projects, whether in medicine, economics, or social sciences. Their ability to dissect complex data sets can lead to breakthrough discoveries or insights that have the potential to influence policy, medical treatments, or industry trends.
  • Consistent Demand for Expertise: As the world becomes increasingly data-driven, the demand for professionals who can understand and interpret this data is growing. Statisticians, with their deep knowledge of data analysis, are consistently sought after, leading to job stability and numerous employment opportunities.
  • Intellectual Fulfillment and Continuous Learning: The nature of statistics involves tackling challenging questions and unraveling complex patterns. This provides statisticians with an intellectually stimulating environment where they can continuously learn, adapt, and refine their skills to address ever-evolving challenges.
  • Direct Impact on Decision Making: Statisticians often play a pivotal role in shaping strategies, policies, or products by providing evidence-based recommendations. Their analyses inform crucial decisions, granting them a significant and influential position within organizations and research teams.

Working Conditions

Statisticians typically work in well-structured and organized environments, whether that’s in academic institutions, government agencies, research facilities, or corporate settings. The core of their job involves dealing with data: collecting, analyzing, and interpreting it using specialized software. 

As such, they often spend substantial periods at their desks, immersed in data modeling, simulation, and computation. Despite the somewhat solitary nature of these tasks, collaboration is a key aspect of their role. Statisticians frequently team up with researchers, policymakers, or business leaders to discuss findings, understand context, or frame analyses. Given the precision required in their work, there’s a strong emphasis on attention to detail.

Further Studies

  • A Master’s degree or Ph.D. is often required for more advanced roles.
  • Proficiency in statistical software such as R or SAS, and programming languages like Python.

What Skills Make You a Strong Candidate

You have excellent mathematical skills, a deep understanding of statistical theories, and proficiency in using statistical software. You are analytical, detail-oriented, and have excellent problem-solving skills. You also have strong communication skills to present their findings to non-technical stakeholders and to explain the methods they used to arrive at their conclusions.

Salary Range & Job Outlook

Average Salary ($95,570)
Job Outlook (31%)

The median annual wage for statisticians was $95,570 in May 2021.

Overall employment of mathematicians and statisticians is projected to grow 31% from 2021 to 2031, much faster than the average for all occupations.

5. Quantitative Analyst

A Quantitative Analyst, often known as a “quant,” applies mathematical and statistical methods to understand, predict, and analyze the behavior of markets and financial instruments. This role is particularly prevalent in finance, where they help firms make investment decisions and manage financial risks.

As a Quantitative Analyst

You’ll typically develop complex mathematical models that financial firms use to make decisions about risk management, investments, and pricing. You use your models to understand the performance of these investments and to create strategies for maximizing returns. You may also be involved in creating algorithms that will be used in automated trading systems.


  • Highly Competitive Compensation: Quantitative analysts, often referred to as “quants” in the finance sector, typically receive lucrative salaries and bonuses due to the specialized nature of their work. Their ability to develop financial models and strategies that directly impact a firm’s profitability makes them invaluable assets, leading to attractive remuneration packages.
  • Intersection of Finance and Technology: Quants get to work at the cutting edge of finance and technology, using sophisticated tools and algorithms to analyze markets. This intersection provides a dynamic and stimulating work environment, combining elements of financial theory with advanced computational techniques.
  • Clear Pathway to Career Progression: Given the critical role they play in investment strategies, risk management, and algorithmic trading, quantitative analysts often find opportunities for upward mobility. Experienced quants can move into senior roles, manage teams, or even transition into high-ranking positions in asset management or hedge funds.
  • Challenging and Intellectually Stimulating: The complexities of financial markets, combined with the intricacies of mathematical modeling, offer quants a consistently challenging landscape. For those with a passion for problem-solving and innovation, the role provides an endless array of intellectually engaging tasks.
  • Global Opportunities and Exposure: The skills and expertise of a quantitative analyst are universally recognized and valued, allowing for opportunities to work in major financial hubs worldwide. This global perspective offers quants exposure to diverse markets, cultures, and financial practices, enriching their professional experience.

Working Conditions

Quantitative analysts, commonly known as “quants”, operate primarily within the high-paced, intense environment of the financial sector. Their typical workspace is often situated in the bustling centers of major cities, within large banks, hedge funds, or proprietary trading firms. Surrounded by multi-monitor setups, quants spend a significant portion of their day developing, testing, and refining mathematical models to predict market movements or manage risks.

While they deal extensively with complex algorithms and computational tools, their role is not isolated; they routinely collaborate with traders, risk managers, and other financial professionals to translate their analytical insights into actionable strategies. The demands of real-time financial markets mean that the job can be high-pressure, especially when immediate responses are required to volatile market conditions

Further Studies

  • Ph.D. can be beneficial especially for complex modeling roles.
  • Familiarity with programming languages such as Python, R, or C++.

What Skills Make You a Strong Candidate

You have strong mathematical and statistical skills, as well as a solid understanding of financial markets. You are skilled in using programming languages and software to model and analyze data. You are highly analytical, detail-oriented, and have strong problem-solving abilities. In addition, excellent communication skills are essential to explain your findings to stakeholders who may not have a technical background.

Salary Range & Job Outlook

Average Salary ($101,197)
Job Outlook (6%)

Salaries have increased 9% for quantitative analysts in the last 5 years in light of the unprecedented growth of analytics technology.

Projected job growth for quantitative analysts is 6% from 2018-2028

The average salary for a quantitative analyst is $101,197.

6. Business Intelligence Analyst

A Business Intelligence Analyst plays a crucial role in transforming data into insights that drive business value. By analyzing data trends, these professionals can help businesses make data-driven decisions and strategize effectively for future growth. Their role sits at the intersection of business operations and data science.

As a Business Intelligence Analyst

You’ll collect data from internal and external sources, prepare detailed reports, and provide actionable insights. You may be responsible for designing, developing, and maintaining BI solutions such as dashboards and reports. In addition, you might perform queries on databases, undertake data quality control, and carry out data profiling to understand how to improve business operations and strategy.


  • Influence Strategic Decision Making: Business intelligence analysts play a pivotal role in guiding organizational strategy by converting raw data into actionable insights. Their analyses directly influence key decisions, from product launches to market expansions, ensuring their work has tangible impacts on the company’s trajectory.
  • Diverse Industry Opportunities: The need for data-driven decision-making is universal across sectors, from healthcare and finance to retail and technology. This means that business intelligence analysts have the flexibility to work in a variety of industries based on their interests and expertise.
  • Continuous Professional Growth: The rapidly evolving landscape of data analytics tools and business intelligence technologies ensures that there’s always something new to learn. This dynamic environment fosters continuous skill enhancement, offering BI analysts opportunities for professional development and specialization.
  • Cross-functional Collaborations: Working in business intelligence often involves liaising with various departments, from marketing and sales to IT and finance. This interdisciplinary interaction provides a holistic view of the organization and enhances collaborative problem-solving, enriching the overall work experience.
  • Competitive Compensation and Job Stability: With businesses increasingly recognizing the value of data-driven insights, the demand for skilled BI analysts remains strong. This demand translates to competitive salaries, benefits, and a stable job market for those with the right expertise and experience.

Working Conditions

Business Intelligence (BI) analysts often find themselves in modern, tech-forward office environments, whether that’s within corporations, startups, or consultancies. Their work primarily revolves around computer systems, using advanced BI software and tools to mine, analyze, and visualize data to provide strategic insights.

While a significant portion of their day is dedicated to data analysis, their role is not confined to this alone. They frequently collaborate with other departments, attending meetings and workshops to understand the specific needs of various teams or to present their findings.

This constant interaction makes effective communication skills as essential as their analytical prowess.. The evolution of remote work and digital collaboration tools also means that many BI analysts have the flexibility to work from various locations, blending office days with remote work.

Further Studies

  • A Master’s degree may be beneficial for advanced positions.
  • Certifications in business intelligence tools such as Power BI, Tableau, or SQL can be advantageous.

What Skills Make You a Strong Candidate

You possess strong analytical and problem-solving skills, and are detail-oriented. You have a deep understanding of data warehouse and database architecture. You are proficient in BI technologies and tools and are an excellent communicator, able to translate complex data findings into understandable documents and reports for business executives. You also often have a good understanding of business operations and industry-specific knowledge.

Salary Range & Job Outlook

Average Salary ($80,249)
Job Outlook (21%)

Salaries have increased 10% for business intelligence analysts in the last 5 years. The average salary for a business intelligence analyst is $80,249.

Projected job growth for business intelligence analysts is 21% from 2018-2028. This impressive job growth comes on the heels of major developments in BI technology, artificial intelligence and machine learning and the integration of such systems into the daily operations of many different businesses and industries.

7. Data Architect

A Data Architect is a visionary who designs and manages the data infrastructure of an organization. They are responsible for visualizing and designing an organization’s enterprise data management framework. This role is crucial in ensuring that the data is stored, managed, and utilized efficiently in a secure environment.

As a Data Architect

You’ll create database solutions that are both robust and scalable to handle the needs of the business. You determine structural requirements by analyzing client operations, applications, and programming. You develop data models for database structures, oversee data-related procedures and plans, and work closely with other IT team members to integrate systems and ensure data consistency.


  • Foundation of Data-driven Enterprises: Data architects play a critical role in shaping how organizations store, access, and manage data. Their designs enable efficient data flow and accessibility, ensuring that businesses can effectively leverage data for decision-making, giving them a central role in modern enterprise success.
  • High Demand and Competitive Compensation: With the rise of big data, cloud computing, and digital transformation, the demand for skilled data architects has soared. This high demand typically translates into attractive salary packages, job stability, and additional perks, reflecting the importance of their role.
  • Opportunities for Continuous Learning: The rapidly evolving technology landscape offers data architects constant opportunities to engage with emerging tools, platforms, and methodologies. This continuous learning environment ensures that they remain at the forefront of technological innovation.
  • Cross-functional Collaborations: Data architects frequently collaborate with a diverse range of professionals, including data scientists, software developers, and business stakeholders. This cross-functional interaction not only enriches their work experience but also ensures holistic solutions that cater to varied organizational needs.
  • Influence on Strategic Decision-making: By ensuring the integrity, reliability, and availability of data, data architects indirectly shape business strategies and decisions. Their expertise guarantees that data-driven insights are grounded in well-structured and dependable data architectures, amplifying their influence on organizational outcomes.

Working Conditions

Data architects operate at the nexus of technology and strategy, typically working in well-equipped, modern office environments that prioritize technological access and collaboration. These professionals spend a considerable amount of their time interacting with complex database systems, cloud platforms, and modeling tools, often using powerful computing setups tailored for intensive tasks. 

While their role involves deep technical immersion, it’s not confined solely to independent work. They frequently engage in meetings, brainstorming sessions, and collaborative projects with various departments, from IT to business strategy teams. As the digital realm is 24/7, there might occasionally be requirements to address urgent system-related issues outside of regular hours, ensuring data accessibility and integrity. 

With the rise of digital collaboration tools and the global nature of data infrastructure, many data architects also have the flexibility to work remotely or in hybrid settings. However, regardless of the physical location, their role demands precision, focus, and a commitment to upholding the highest standards of data management and security.

Further Studies

  • Master’s degree may be beneficial for more advanced roles.
  • Proficiency in database languages such as SQL.

What Skills Make You a Strong Candidate

You have excellent technical skills, including experience with database design, data analysis, SQL, and cloud-based platforms. You have strong problem-solving abilities, an understanding of data warehousing, and data modeling skills. You also have excellent communication and leadership skills, as you often have to coordinate with different teams and explain complex concepts to non-technical stakeholders.

Salary Range & Job Outlook

Average Salary ($123,430)
Job Outlook (9%)

The median annual wage for database architects was $123,430 in May 2021.

Overall employment of database administrators and architects is projected to grow 9% from 2021 to 2031, faster than the average for all occupations.

8. Machine Learning Engineer

A Machine Learning Engineer is a type of computer programmer that uses algorithms and statistical models to help computer systems improve at tasks with minimal human intervention. The role combines computer science, data analysis, and applied research, making it one of the most exciting fields in data science today.

As a Machine Learning Engineer

You’ll design and implement machine learning systems. They run machine learning tests and experiments, perform statistical analysis, and fine-tune test results. They are also responsible for training and retraining systems when necessary, and scaling machine learning solutions to match business needs. In some cases, they might also build and maintain scalable machine learning solutions in production.


  • Frontline of Technological Innovation: Machine learning engineers have the unique opportunity to work at the cutting edge of technology, developing algorithms and models that power transformative applications, from autonomous vehicles to personalized medicine. Their work often redefines industry boundaries and pushes the envelope of what’s possible.
  • High Demand and Lucrative Compensation: With industries increasingly realizing the potential of AI and machine learning, there’s a soaring demand for skilled machine learning engineers. This demand often translates into competitive salary packages, generous benefits, and job stability, reflecting the critical nature of their expertise.
  • Diverse Application Across Sectors: Machine learning is not confined to a single domain. Engineers in this field can apply their skills across a multitude of sectors, including healthcare, finance, entertainment, and agriculture. This versatility allows them to explore varied challenges and solutions, ensuring a dynamic career path.
  • Continuous Learning and Professional Growth: The field of machine learning is continually evolving, with new techniques, tools, and challenges emerging regularly. This dynamic landscape offers engineers opportunities for perpetual learning, skill enhancement, and specialization in niche areas of interest.
  • Tangible Impact on Real-world Problems: Machine learning engineers often work on projects that address pressing global issues, from climate change modeling to early disease detection. Their expertise can directly contribute to solutions with significant societal impact, offering a sense of purpose and fulfillment in their roles.

Working Conditions

Machine learning engineers operate within the rapidly evolving realm of artificial intelligence, often situated in tech-centric environments that prioritize innovation and collaboration. Their workspace is frequently characterized by high-performance computing setups, granting them access to the necessary tools and resources to build, test, and refine complex algorithms. 

Given the interdisciplinary nature of machine learning, these engineers often work closely with data scientists, software developers, and domain experts, fostering a collaborative atmosphere. While a significant portion of their time is dedicated to coding and model development, they also engage in research, brainstorming sessions, and presentations, bridging the gap between theoretical advancements and practical applications.

Further Studies

What Skills Make You a Strong Candidate

You are proficient in several programming languages, have deep knowledge of machine learning, understand complex algorithms, and can work with big data. You are analytical, have good problem-solving abilities, and are familiar with software architecture and engineering. Excellent communication skills are also important, as you’ll often need to explain your work and collaborate with other team members.

Salary Range & Job Outlook

Average Salary ($131,490)
Job Outlook (21%)

The US Bureau of Labor Statistics projects the job market for computer and information research scientists (including ML engineers) to grow by 21% from 2021 to 2031, dwarfing the 5% average growth rate for all occupations. The median annual wage for computer and information research  scientists was $131,490 in May 2021. The surprising growth rate lies with the significant growth in AI and machine learning technologies that are continuing to shatter job growth expectations and open the doors to many lucrative careers.

9. Big Data Engineer

A Big Data Engineer specializes in creating, managing, and optimizing big data infrastructure and tools. They are often involved in the design and development of a big data environment and the pipelines needed to support large-scale data processing and analysis.

As a Big Data Engineer

You’ll design, build, and manage big data infrastructures and tools. You’ll develop data processing algorithms and deploy predictive models. You’ll also collaborate with data scientists and other stakeholders to ensure data solutions are in line with business needs. You may also be involved in troubleshooting any issues with the data systems and ensuring the integrity and security of big data.


  • Central Role in Modern Enterprises: Big data engineers are pivotal in enabling businesses to harness the power of massive datasets. By constructing and maintaining the data infrastructure, they allow organizations to glean insights, make informed decisions, and gain a competitive edge in today’s data-driven market.
  • High Demand and Attractive Compensation: As businesses increasingly rely on big data solutions, the demand for skilled big data engineers has surged. This demand translates into impressive salary packages, job stability, and a range of career opportunities, reflecting the value of their specialized expertise.
  • Continuous Learning and Skill Development: The realm of big data is dynamic, with new tools, platforms, and techniques emerging regularly. For big data engineers, this ensures a career filled with opportunities for learning, upgrading skills, and staying at the forefront of technological advancements.
  • Diverse Challenges and Problem Solving: Handling vast volumes of data brings unique challenges, from scalability issues to real-time processing needs. Addressing these challenges allows big data engineers to engage in varied, intellectually stimulating tasks, ensuring that their role remains invigorating and fulfilling.
  • Opportunities Across Industries: Big data isn’t restricted to a particular sector. Engineers specializing in this domain find opportunities in healthcare, finance, entertainment, retail, and beyond. This industry-spanning demand offers them the chance to work on a multitude of projects, broadening their experience and exposure.

Working Conditions

Big data engineers often find themselves immersed in high-tech environments tailored for data-intensive tasks. Their day-to-day operations primarily revolve around designing, implementing, and managing large-scale data pipelines, necessitating access to powerful computing clusters and state-of-the-art software tools. 

While much of their work demands focused, individual attention to intricate technical details, collaboration is equally vital. They regularly interact with data scientists, business analysts, and IT teams, ensuring that the data infrastructure aligns with organizational needs and supports analytic endeavors. 

There’s an implicit expectation for big data engineers to maintain systems with high availability and reliability. This responsibility can sometimes lead to extended or irregular hours, especially during system upgrades or when addressing unforeseen challenges. However, the evolving nature of the tech industry also means that many big data engineers enjoy flexibility, with options for remote work, comfortable office settings, and access to advanced digital collaboration tools.

Further Studies

  • Advanced knowledge of big data technologies like Hadoop, Spark, and Kafka.
  • Proficiency in programming languages such as Python, Java, or Scala.

What Skills Make You a Strong Candidate

You have excellent analytical and problem-solving skills, with a deep understanding of data architecture and big data technologies. You possess strong programming skills and are familiar with data interface protocols. You also need to be proactive, with good communication skills to collaborate with various teams and explain complex data infrastructures in simple terms.

Salary Range & Job Outlook

Average Salary ($174,394)
Job Outlook (22%)

As of June 19, 2023, the average annual pay for a Big Data Solutions Architect in the United States is $174,394 a year. The projected job growth for big data engineers is 22% between 2020 and 2030.

10. Data Visualization Specialist

Data Visualization Specialists collect, process, and clean data for analysis. They design, create, and develop data-driven visuals that effectively represent complex data to a non-technical audience. They also collaborate with different teams to identify trends and relationships in the data, which can be critical to business strategies and decisions.

As a Data Visualization Specialist

You’ll collect, process, and clean data for analysis. You design, create, and develop data-driven visuals that effectively represent complex data to a non-technical audience. You also collaborate with different teams to identify trends and relationships in the data, which can be critical to business strategies and decisions.


  • Bridging Data and Decision-making: Data visualization specialists play an essential role in translating complex data into comprehensible visual formats. Their creations empower decision-makers to grasp intricate patterns, trends, and insights easily, making the specialist’s work pivotal for data-driven strategies.
  • High Demand Across Multiple Sectors: As data becomes a cornerstone of decision-making in various industries, the demand for experts who can visualize this data effectively is on the rise. Whether in healthcare, finance, marketing, or public policy, their skills are sought after, offering diverse opportunities.
  • Merging Creativity with Technology: This role offers a unique blend of art and science, allowing specialists to exercise their creativity while working with advanced technological tools. Crafting compelling visuals that convey complex information offers both intellectual and artistic satisfaction.
  • Continuous Learning and Development: The tools and techniques in data visualization are ever-evolving, with new software and design principles emerging regularly. This dynamic landscape offers specialists constant opportunities for skill enhancement and exploring innovative ways to represent data.
  • Collaborative Work Environment: Data visualization specialists often work in tandem with data scientists, analysts, business stakeholders, and designers. This collaborative setting allows for a richer understanding of project goals and fosters interdisciplinary growth and learning.

Working Conditions

Data visualization specialists operate at the intersection of design, technology, and data science. Their working environment is typically a blend of modern tech spaces and creative studios. Equipped with powerful computing systems and access to premium visualization software, these specialists spend significant time converting raw data into engaging, insightful visuals.

While much of their role requires focused solitary work, particularly during the design phase, it is inherently collaborative. Regular interactions with data analysts, researchers, and business stakeholders are common, ensuring that visuals align with both data insights and business objectives. Due to the iterative nature of design, feedback sessions and revisions are integral parts of their workflow. 

With the rise of remote working tools and digital collaboration platforms, many data visualization specialists also have the flexibility to work from different locations, blending in-office collaboration with remote design sessions. The role demands precision, a keen eye for aesthetics, and a deep understanding of how visuals can impact decision-making.

Further Studies

  • Knowledge of data visualization tools like Tableau, PowerBI, or D3.js is critical.
  • Proficiency in programming languages such as Python or R, particularly for creating complex visualizations.

What Skills Make You a Strong Candidate

You have a combination of technical skills and creative flair. You have a deep understanding of data analysis and are skilled in using visualization tools. You also have strong design and aesthetic sense to create compelling visuals. In addition, you have excellent communication skills to work with different teams and present their findings to both technical and non-technical audiences.

Salary Range & Job Outlook

Average Salary ($96,838)
Job Outlook (36%)

The average Data Visualization Specialist salary is $96,838 as of May 25, 2023. Employment of data scientists is projected to grow 36% from 2021 to 2031, much faster than the average for all occupations. With the rise of AI, NLP and similar technologies, data visualization specialists are in high demand to interpret the information that these programs collect.

11. Data and Analytics Manager

A Data and Analytics Manager oversees the data management and analytics practices within an organization. They develop and implement strategies to manage data collection, data analysis, and reporting. Their role is crucial in ensuring that data is accurate, secure, and used effectively to drive business decisions.

As a Data and Analytics Manager

You’ll design and implement data strategies and systems, and ensure the quality and accuracy of data. You manage a team of data professionals, overseeing their activities in data processing, analysis, modeling, and reporting. You also collaborate with other teams to identify opportunities for leveraging data to drive business solutions.


  • Driving Business Strategies: As a data and analytics manager, individuals have the power to shape key business decisions by converting raw data into actionable insights. Their expertise ensures that strategies are grounded in empirical evidence, leading to more informed and effective outcomes.
  • High Demand and Competitive Compensation: The modern business landscape recognizes the immense value of data-driven decision-making. This has catapulted the demand for skilled data and analytics managers, translating into attractive salary packages, robust benefits, and career advancement opportunities.
  • Cross-functional Collaborations: These managers often work closely with various departments within an organization, from marketing and finance to operations and IT. This exposure to multiple business facets fosters a holistic understanding of the enterprise and encourages interdisciplinary knowledge exchange.
  • Continuous Skill and Knowledge Enhancement: The dynamic nature of data analytics means that there are always new tools, technologies, and methodologies emerging. This ensures that data and analytics managers are consistently learning and staying at the cutting edge of industry advancements.
  • Leadership and Team Development: In their managerial role, these professionals are not just responsible for data but also for guiding and nurturing their team. This offers the dual satisfaction of contributing to business successes and playing a pivotal role in the professional growth of team members.

Working Conditions

Data and analytics managers function in a dynamic, fast-paced environment where data is at the heart of decision-making. Typically based in modern office settings equipped with advanced technological tools, these managers oversee teams responsible for collecting, processing, and interpreting vast amounts of information.

While their role demands a deep understanding of data tools and techniques, it’s equally centered on leadership; they are often tasked with guiding their teams, setting project directions, and ensuring timely deliverables. Collaborative efforts are a staple, as they liaise with various other departments, integrating feedback and ensuring that the insights derived align with broader business goals.

Further Studies

  • Proficiency in data analysis tools and programming languages such as SQL, R, or Python.

What Skills Make You a Strong Candidate

You are experienced in managing and analyzing data, and have a deep understanding of the data landscape. You possess excellent leadership skills, with the ability to manage and mentor a team. You also have strong strategic thinking abilities, excellent problem-solving skills, and can communicate effectively with both technical and non-technical stakeholders.

Salary Range & Job Outlook

Average Salary ($159,010)
Job Outlook (16%)

The median annual wage for computer and information systems managers was $159,010 in May 2021.

Employment of computer and information systems managers is projected to grow 16% from 2021 to 2031, much faster than the average for all occupations. With the continuing accelerated rise of technologies in many different industries and disciplines, the demand for computer and information systems managers has surged given the necessity to manage and analyze all of the information collected.

12. Bioinformatician

A Bioinformatician utilizes computational tools to gather, analyze, and interpret complex biological data. They play a pivotal role in fields such as genomics, proteomics, and drug discovery, where they decipher large volumes of biological data to understand biological systems, diseases, and potential

As a Bioinformatician

You’ll develop and apply computational tools and algorithms to analyze biological data. In this role, you interpret complex biological data, including genomic data, and may work on sequencing genomes, analyzing genetic mutation, predicting protein structure and function, as well as integrating clinical and genomics data for personalized medicine.


  • Contributing to Groundbreaking Research: Bioinformaticians stand at the forefront of modern biological and medical research. Their expertise in analyzing complex biological data helps in advancing our understanding of genetics, diseases, and evolutionary patterns, making their work integral to scientific breakthroughs.
  • Interdisciplinary Exposure: Bioinformatics seamlessly blends biology, computer science, and mathematics. This interdisciplinary nature ensures that bioinformaticians are continually learning and integrating diverse knowledge sets, keeping their work both challenging and intellectually stimulating.
  • High Demand in Both Academia and Industry: With the explosion of genomic data and the rise of personalized medicine, bioinformaticians are in high demand in research institutions, pharmaceutical companies, and biotech startups. This demand offers robust job prospects and competitive compensation packages.
  • Potential for Real-world Impact: The insights derived by bioinformaticians can directly influence medical treatments, drug development, and disease prevention strategies. This offers them the satisfaction of knowing their work has tangible benefits for patients and society at large.
  • Continuous Technological Advancement: The field of bioinformatics is ever-evolving, with new computational tools, algorithms, and data storage solutions emerging regularly. This dynamic landscape ensures that bioinformaticians are always at the cutting edge of technology, driving innovation and enhancing their skill set.

Working Conditions

Bioinformaticians operate at the nexus of biology and computational science, often situated in environments that foster both academic rigor and technological innovation. Their typical work settings range from state-of-the-art laboratories in research institutions to modern office spaces in biotech companies. Given the computational nature of their tasks, they spend considerable time in front of high-performance computer systems, analyzing vast biological datasets. 

They frequently interact with molecular biologists, geneticists, and other specialists to ensure data accuracy and relevance. These discussions often lead to brainstorming sessions, team meetings, and, in academic settings, seminars or lectures. With the growing volume of biological data, bioinformaticians might face the pressure of managing and analyzing datasets within tight deadlines, especially if the data is critical for ongoing research or medical treatments. The tools and software they use are constantly evolving, necessitating continuous learning and adaptation.

Further Studies

  • A Ph.D. is often required for advanced roles, particularly in research.

What Skills Make You a Strong Candidate

You have a blend of skills in biology and computer science. You possess excellent analytical skills, a deep understanding of genetics and molecular biology, and are proficient in bioinformatics tools and programming languages. You are detail-oriented, with excellent problem-solving skills, and have the ability to work on complex biological problems. Good communication skills are also crucial to present their findings to non-technical stakeholders.

Salary Range & Job Outlook

Average Salary ($88,553)
Job Outlook (15.2%)

The market size of bioinformatics services was USD 2.50 billion in 2021, and it is projected to experience a revenue CAGR of 15.2% over the forecast period. The growth in demand for bioinformatics services in biotechnology research and drug discovery is propelling market revenue growth.

The average Bioinformatician salary in the United States is $88,553.

13. Database Administrator

A Database Administrator (DBA) is a professional who manages, monitors, and maintains an organization’s databases. Their role is critical in ensuring data is secure, organized, and accessible to meet the needs of the organization. They ensure databases run efficiently and are safeguarded against unauthorized access or malicious actions.

As a Database Administrator

You are responsible for installing, configuring, upgrading, administering, monitoring, and maintaining databases in an organization. You ensure the database is optimized and backup procedures are in place. You also troubleshoot any issues related to the database and implement security measures to protect data.


  • Critical Role in Modern Enterprises: Database administrators (DBAs) are the gatekeepers of an organization’s data, ensuring that databases run efficiently, securely, and without interruption. Their work is pivotal for the smooth operation of businesses, making their role indispensable in a data-driven world.
  • Competitive Compensation and Job Security: Given the rising reliance on data storage and management in today’s digital age, DBAs are in high demand. This demand translates into attractive salary packages, comprehensive benefits, and long-term job stability.
  • Diverse Challenges and Continuous Learning: The dynamic nature of database technologies means that DBAs are always encountering new challenges, from migrating to new platforms to implementing advanced security protocols. This ensures that their job remains intellectually stimulating and offers continuous opportunities for skill enhancement.
  • Cross-functional Collaborations: Database administrators often collaborate with various departments, from IT and software development to business analysis and management. This engagement across different teams fosters a broader understanding of organizational operations and encourages diverse interactions.
  • Potential for Career Advancement: As DBAs gain experience and demonstrate expertise, they have opportunities to progress into senior roles, such as database architects or managers, or transition into related fields like data analytics or IT management. This growth potential ensures a promising and versatile career path.

Working Conditions

Database administrators (DBAs) operate primarily in office settings, often within the IT departments of organizations. Their roles are grounded in ensuring the efficient, secure, and smooth operation of database systems. These professionals work extensively on computers, using specialized software to monitor, maintain, backup, and sometimes restore databases. The nature of their responsibilities might require them to work outside typical business hours, especially when database updates or maintenance tasks need to be performed during times of minimal user activity. They often collaborate with other IT professionals, such as network administrators or developers, to ensure that the databases integrate seamlessly with other systems. Due to the criticality of data in modern businesses, DBAs might be on-call to address urgent issues that arise unexpectedly, ensuring data availability and integrity. While much of their work is independent, effective communication skills are vital, as they frequently interact with non-technical stakeholders to gather requirements or explain database complexities.

Further Studies

  • Master’s degree can be beneficial for advancement.

What Skills Make You a Strong Candidate

You have a deep understanding of database structures, theories, principles, and practices. You are skilled in database languages like SQL, have excellent problem-solving abilities, and are detail-oriented. You also have a keen understanding of database security and backup procedures. Good communication skills are crucial for collaborating with other IT professionals and explaining database issues to non-technical stakeholders.

Salary Range & Job Outlook

Average Salary ($96,710)
Job Outlook (9%)

The median annual wage for database administrators was $96,710 in May 2021.Overall employment of database administrators and architects is projected to grow 9% from 2021 to 2031, faster than the average for all occupations.

14. Predictive Modeler

A Predictive Modeler is a professional who uses statistics, data mining, and modeling techniques to create predictive models. These models are used to forecast future outcomes, trends, or behaviors based on historical and current data. Predictive modeling is prevalent in numerous fields, such as finance, marketing, healthcare, and insurance.

As a Predictive Modeler

You collect and analyze data, apply statistical methods, and create predictive models. You also test and validate models to ensure their reliability and accuracy. You then interpret the model results, communicate findings to stakeholders, and apply the insights to solve complex business problems.


  • High Impact Decision-making: As a predictive modeler, professionals play a pivotal role in shaping business strategies by using historical data to forecast future trends, allowing companies to make informed and proactive decisions based on data-driven insights.
  • Growing Demand Across Industries: Predictive modeling is not confined to one sector; from finance and healthcare to retail and e-commerce, numerous industries recognize the value of forward-looking analytics. This widespread applicability ensures diverse opportunities and job security for modelers.
  • Continuous Skill Enhancement: The realm of predictive modeling is ever-evolving, with emerging techniques, algorithms, and software tools. This dynamic environment offers modelers the chance to constantly update their skills and stay abreast of the latest advancements in data science.
  • Interdisciplinary Collaborations: Predictive modelers often work alongside marketers, financial analysts, IT specialists, and other professionals. These collaborations offer a broader perspective on business operations and encourage holistic problem-solving approaches.
  • Competitive Compensation: Given the tangible benefits businesses derive from accurate predictions – be it in optimizing marketing campaigns or streamlining operations – predictive modelers are often rewarded with attractive salary packages and benefits commensurate with their significant contributions.

Working Conditions

Predictive modelers often find themselves embedded in the vibrant hub of an organization’s analytical team, usually working in well-equipped, modern office environments. Given the data-intensive nature of their job, they spend significant amounts of time on powerful computing setups, using specialized software to sift through datasets and develop predictive algorithms. 

Their tasks are a blend of individual-focused deep analyses and collaborative efforts, as they frequently consult with other professionals, such as data engineers, business analysts, and domain experts, to ensure the accuracy and relevance of their models.

Further Studies

  • Master’s degree or Ph.D. can be beneficial for advanced roles.
  • Proficiency in statistical and programming languages such as R, Python, or SAS.
  • Knowledge of machine learning techniques and predictive modeling tools.

What Skills Make You a Strong Candidate

You have excellent mathematical and statistical skills, a deep understanding of predictive modeling techniques, and proficiency in using modeling tools. You are analytical, detail-oriented, and have excellent problem-solving skills. You also have strong communication skills and are able to present your findings to non-technical stakeholders as well as explain the methodologies behind your models.

Salary Range & Job Outlook

Average Salary ($113,277)

The average Predictive Modeler salary is $113,277 as of May 25, 2023. As this is a relatively new field, there are currently no job growth predictions or statistics available.

15. Geospatial Professional

A Geospatial Professional specializes in collecting, analyzing, and interpreting geographic data. They use Geographic Information System (GIS) technology to visualize, measure, and analyze spatial data, contributing to fields such as urban planning, environmental science, transportation, and more.

As a Geospatial Professional

You’ll collect and analyze spatial data, use GIS software to create maps, charts, or diagrams, and perform spatial analyses and modeling. You’ll also manage GIS databases and collaborate with other teams to support their geospatial data needs. Your role might involve working on tasks like identifying patterns and trends in data, spatial problem-solving, or satellite imagery analysis.


  • Multifaceted Applications: As a geospatial professional, individuals have the opportunity to work on a myriad of projects, from environmental conservation and urban planning to disaster management and transportation logistics. The wide range of applications ensures a varied and stimulating career.
  • Contribution to Sustainable Development: Geospatial professionals play a crucial role in environmental and urban planning initiatives, helping societies make data-driven decisions that promote sustainable growth and reduce ecological footprints.
  • Technological Advancement: The field of geospatial science is rapidly evolving, with constant innovations in satellite technologies, geographic information systems (GIS), and remote sensing techniques. This continuous growth offers professionals the chance to work with cutting-edge tools and expand their expertise.
  • High Demand in Diverse Industries: With the growing recognition of spatial data’s importance, geospatial expertise is sought after in numerous sectors, including government agencies, real estate, defense, and public health. This wide-ranging demand ensures robust job prospects and career stability.
  • Opportunity for Field Work: Unlike many professions confined to office settings, geospatial roles often include fieldwork components, allowing professionals to experience different terrains, cultures, and environments, enriching their work experience and broadening their perspectives.

Working Conditions

Geospatial professionals operate at the crossroads of technology and geography, with working conditions that vary based on specific projects and roles. While a substantial portion of their work might take place in an office environment, utilizing powerful software to analyze spatial data and create detailed maps, there’s also a significant emphasis on fieldwork. This could involve collecting data on-site using GPS devices, drones, or other remote sensing equipment, sometimes in challenging terrains or weather conditions. These outdoor excursions demand adaptability and a keen sense of observation. 

Back in the office, they often collaborate closely with urban planners, environmental scientists, and policymakers, ensuring that their spatial insights translate into actionable strategies. The work can be deadline-driven, especially when addressing time-sensitive issues like disaster response or environmental crises. Continuous professional development is a hallmark of the role, given the rapid advancements in geospatial technologies. The balance of analytical tasks, collaborative projects, and on-ground data collection provides a dynamic and multifaceted work environment for geospatial experts.

Further Studies

  • Proficiency in GIS software such as ArcGIS or QGIS, and programming languages like Python.

What Skills Make You a Strong Candidate

Ideally, you have excellent analytical skills, a deep understanding of GIS, and proficiency in using GIS software. You are detail-oriented, have superb problem-solving skills, and a strong geographical knowledge. Good communication skills are also crucial to present their findings to non-technical stakeholders and explain the methodologies used.

Salary Range & Job Outlook

Average Salary ($62,823)
Job Outlook (5%)

The job market for analysts is projected to grow 5% from 2018 to 2028. The median salary for geospatial professionals is $62,823.

Making the Right Career Choice

Choosing the right career path is a critical decision, especially in a field as vast and multifaceted as data science. Each role comes with its unique set of responsibilities, benefits, and challenges, allowing individuals to find a niche that aligns with their skills, interests, and long-term career aspirations.

However, the diversity of roles in data science also requires careful self-assessment. Prospective data science professionals should not only consider their academic qualifications and technical skills but also their interests, values, and long-term career goals. It’s crucial to consider questions such as: Do you enjoy deep, analytical thinking and complex problem-solving? Are you interested in turning raw data into actionable insights? Are you intrigued by the possibilities of machine learning, or do you find more satisfaction in creating visually compelling representations of data? Your answers to these questions will help guide you toward the role that suits you best.