All models are wrong, but some are useful.
George E. P. Box, British statistician
Almost every major industry in the United States has careers and job opportunities for statisticians. From healthcare and scientific research to finance, technology, public policy, and manufacturing, an increasing number of organizations are looking to data to make strategic decisions. This means that the demand for professionals with statistical and analytical skills is growing. Here are 10 of the most desirable, high-impact careers for statistics or math graduates, particularly those with graduate degrees.
| Job Title | What They Do | Required Qualifications | Average Salary (US) | Useful Notes |
| Statistician | Analyze data, design studies, build models, and communicate insights across sectors. | Bachelor’s or Master’s in Statistics or related field. | $80,000–$110,000 | High job stability; strong demand in government, healthcare, and research. |
| Biostatistician | Apply statistical methods to public health, medicine, and clinical research. | Master’s in Biostatistics, Statistics, or Public Health; PhD preferred for research. | $90,000–$120,000 | Key role in medical advancements; strong growth in pharma & public health. |
| Data Analyst (Statistics-Focused) | Clean, analyze, visualize data, and support data-driven business decisions. | Bachelor’s in Statistics, Data Science, or related field. | $65,000–$90,000 | Entry-level gateway into data careers; strong upward mobility. |
| Data Scientist | Develop predictive models, machine learning algorithms, and analytical solutions. | Master’s in Data Science, Statistics, or Computer Science recommended. | $100,000–$140,000 | One of the highest-paid data roles; strong demand in tech and research. |
| Quantitative Analyst | Create financial models, risk assessments, and trading algorithms. | Master’s or PhD in Statistics, Mathematics, Finance, or related fields. | $120,000–$170,000 | Extremely competitive; highest salaries in finance and trading. |
| Statistical Programmer / Statistical Analyst | Write statistical code, prepare datasets, automate workflows, and support research. | Bachelor’s or Master’s in Statistics, Computer Science, or related field. | $75,000–$110,000 | Critical in clinical trials; strong SAS and R skills required. |
| Survey Statistician | Design surveys, develop sampling plans, and analyze survey-based data. | Bachelor’s or Master’s in Statistics, Survey Methodology, or Social Science. | $70,000–$100,000 | Central to national surveys and public opinion research. |
| Government / Federal Statistician | Produce national statistics, conduct policy-relevant research, and analyze major datasets. | Bachelor’s or Master’s in Statistics, Economics, or Public Policy. | $85,000–$120,000 | Most roles at federal agencies; excellent benefits and job security. |
| Industrial / Quality Statistician | Use experiments and statistical tools to improve manufacturing quality and processes. | Bachelor’s or Master’s in Industrial Statistics, Engineering, or related fields. | $75,000–$115,000 | Ideal for manufacturing and engineering sectors; DOE skills essential. |
| Market Research Statistician | Analyze consumer behavior, market trends, and product performance data. | Bachelor’s or Master’s in Statistics, Marketing Analytics, or related fields. | $60,000–$95,000 | Important for marketing, advertising, and consumer insights. |
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1. Statistician
Statisticians are the core of data analysis. Their roles include designing studies, analyzing complex datasets, and providing insights. Their work influences decisions in healthcare, business, government, research, and tech. Their skills can apply to almost any industry, so they have excellent job stability and long-term demand.
Statistician
What They Do:
Statisticians analyze data, design experiments or surveys, build models, and interpret results for decision-making. They assess uncertainty, forecast, and translate findings so that non-technical teams can act on their recommendations.
Required Qualifications:
Most entry-level roles require a bachelor’s degree in statistics, mathematics, or a related field. However, a master’s degree is increasingly preferred, especially for positions in research, policy, or advanced analytics.
Average Salary (US):
Most statisticians earn between $80,000 and $110,000, with higher salaries available in finance, federal government roles, and specialized research positions.
Useful Notes:
This is one of the most versatile career paths in statistics and offers excellent stability. Demand is projected to grow significantly as organizations rely more heavily on data-driven decision-making.
Which statistics job is right for you?
Many students are surprised by how varied statistics careers can be, so identifying the right role often depends on your interests, preferred environment, and long-term goals. Some positions focus on applied data work, while others are more research-driven, programming-heavy, or industry-specific. Understanding the core responsibilities of each job can help you choose a path that matches your strengths and the type of work you enjoy.
2. Biostatistician
Biostatisticians use statistical methods in health, medicine, biotechnology, and public health research. They support clinical trials, epidemiological studies, medical treatments, and patient safety evaluations. Healthcare research requires reliable data, so biostatisticians are in demand in both the private and public sectors.
Biostatistician
What They Do:
Biostatisticians design clinical trials, analyze patient outcomes, evaluate treatment effectiveness, and collaborate with researchers, clinicians, and medical teams. They often contribute to studies that influence medical guidelines, health policies, and new drug approvals.
Required Qualifications:
Most biostatistics roles require a master’s degree in biostatistics, statistics, public health, or a similar quantitative field. Many research and pharmaceutical positions prefer candidates with a PhD or strong research experience.
Average Salary (US):
Biostatisticians typically earn between $90,000 and $120,000, with higher salaries for roles in pharmaceuticals, biotechnology, or supervisory positions.
Useful Notes:
This career path is ideal for students who enjoy both data and medicine. Biostatisticians often work on long-term research studies, contribute to life-saving healthcare decisions, and collaborate in interdisciplinary scientific environments.
3. Data Analyst (Statistics-Focused)
Statistic-focused data analysts apply quantitative methods to discover patterns, support decision-making, and provide actionable insights. This is an excellent role for graduates moving into data careers. Many go on to become senior analysts, data scientists, or specialized statisticians.
Data Analyst
What They Do:
Data analysts clean and prepare datasets, run statistical tests, create visualizations, and present findings to help teams understand trends or performance. Their daily work may involve dashboards, exploratory analysis, and supporting departments such as finance, marketing, operations, or research.
Required Qualifications:
Most roles require a bachelor’s degree in statistics, data science, mathematics, or a related field. Experience with SQL, R, Python, or visualization tools can significantly strengthen a candidate’s profile.
Average Salary (US):
Data analysts commonly earn between $65,000 and $90,000, depending on experience, industry, and technical specialization.
Useful Notes:
This role provides an excellent entry point into the broader analytics world. Many analysts move into more advanced statistical or machine learning positions after gaining experience and expanding their technical toolkit.
4. Data Scientist
Data scientists are interdisciplinary specialists focusing on statistics, computer science, and advanced analytics. Their role involves building predictive models, developing machine learning solutions, and solving complex problems. Their work often influences product development, forecasting, and strategic planning, making them some of the most sought-after and best-paid data professionals.
Data Scientist
What They Do:
Data scientists develop machine learning models, run experiments, test hypotheses, and create end-to-end analytical solutions. Their work involves gathering data, building features, training models, evaluating performance, and communicating insights to technical and non-technical teams.
Required Qualifications:
Most employers look for a master’s degree in data science, statistics, computer science, or a similar quantitative field. Strong programming skills in Python or R, knowledge of machine learning algorithms, and experience working with large datasets are essential.
Average Salary (US):
Data scientists usually earn between $100,000 and $140,000, with higher compensation in technology, finance, and scientific research companies.
Useful Notes:
This is one of the highest-impact roles for graduates with strong statistical and coding skills. The field evolves quickly, so success often requires ongoing learning, experimentation, and familiarity with new tools or modeling techniques.
Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question.
John W. Tukey, American mathematical statistician
5. Quantitative Analyst
Quantitative analysts, or quants, use advanced mathematics, probability, and statistical models to solve financial and risk-related problems. Quants influence trading strategies, investment decisions, and risk management. Since this is a technically demanding role with significant economic impact, it's highly competitive and well-paid.
Quantitative Analyst
What They Do:
Quants build pricing models, run simulations, evaluate market risks, and develop algorithms used in trading and portfolio management. Many are involved in forecasting financial trends, optimizing investment decisions, or supporting automated trading systems.
Required Qualifications:
Most quantitative analyst roles require a master's degree or a PhD in statistics, mathematics, financial engineering, or a related quantitative field. Strong abilities in Python, R, Matlab, probability theory, and stochastic processes are essential, along with knowledge of financial markets.
Average Salary (US):
Quantitative analysts typically earn between $120,000 and $170,000, with senior or specialized roles earning significantly higher compensation.
Useful Notes:
This career path suits students who enjoy challenging mathematical work and fast-paced environments. The field rewards strong analytical thinking, attention to detail, and the ability to translate complex models into practical financial insights.
Top Industries Hiring Statistics for Graduates
Statistics professionals are needed in a wide range of industries, including healthcare, finance, government, technology, and scientific research. Each sector values statistical skills for different reasons, such as improving patient outcomes, understanding markets, building predictive tools, or informing public policy. Knowing which industries align with your skills and interests can help you target the roles that offer the best growth and career satisfaction.
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6. Statistical Programmer / Statistical Analyst
Statistical programmers help research teams, clinical trials, and analytical departments. They build the code and workflows for statistical analysis. Their work enables accurate data processing, correct model execution, and reports that meet regulatory or scientific standards.
Statistical Programmer / Statistical Analyst
What They Do:
Statistical programmers clean and prepare datasets, write scripts in languages such as SAS, R, or Python, automate analysis pipelines, and generate validated reports. In clinical research, they help produce tables, listings, and figures that support regulatory submissions and scientific publications.
Required Qualifications:
The role usually requires a bachelor’s or master’s degree in statistics, computer science, data science, or a similar quantitative field. Experience with statistical software, data management, reproducible workflows, and documentation is highly valuable.
Average Salary (US):
Statistical programmers commonly earn between $75,000 and $110,000, depending on their technical expertise and the industry they work in.
Useful Notes:
This position is ideal for students who enjoy programming and want to work closely with data infrastructure. It is also a strong career path for those who prefer technical execution over client-facing or advisory work.
7. Survey Statistician
Survey statisticians are responsible for designing, conducting, and analyzing surveys. Their work supports decision-making across government, education, the social sciences, public policy, and market research. Thanks to their work, surveys produce reliable, meaningful data.
Survey Statistician
What They Do:
Survey statisticians develop sampling plans, craft questionnaires, manage data collection, and analyze results to draw valid conclusions. They address challenges such as nonresponse, sampling error, and survey weighting, all of which affect the accuracy of final estimates.
Required Qualifications:
These roles often require a bachelor’s or master’s degree in statistics, survey methodology, mathematics, sociology, or a related field. Strong knowledge of sampling methods, statistical modeling, and software such as R, Stata, or SAS is preferred.
Average Salary (US):
Survey statisticians usually earn between $70,000 and $100,000, with higher salaries in federal agencies and specialized research institutions.
Useful Notes:
This career is critical across areas such as national statistics, public opinion research, and social policy. Students who enjoy methodological work, population studies, or designing data collection strategies often excel here.
8. Government / Federal Statistician
Playing a central role in producing datasets to guide national policy, economic planning, health programs, labor analysis, and population research, government and federal statisticians work on some of the largest statistical projects in the country. They often contribute to the reports used by lawmakers, researchers, and the public. These roles are typically very stable.
Government / Federal Statistician
What They Do:
Federal statisticians analyze national survey data, produce official statistics, evaluate policy impacts, and support major research initiatives. They work with large-scale datasets that measure employment, healthcare, housing, education, agriculture, and economic trends.
Required Qualifications:
Most positions require a bachelor's or master's degree in statistics, mathematics, economics, public policy, or a related field. Knowledge of survey methods, regression modeling, and data ethics is essential, as is experience with statistical software such as SAS, R, or Stata.
Average Salary (US):
Government statisticians typically earn between $85,000 and $120,000, depending on agency, seniority, and specialization.
Useful Notes:
These roles offer excellent job stability, substantial benefits, and opportunities to work on meaningful, high-impact projects. Students interested in public service, policy research, or large-scale data systems often find federal statistics work rewarding.
9. Industrial / Quality Statistician
Industrial and quality statisticians focus on helping manufacturing companies improve processes, reduce defects, and ensure products meet safety and performance standards. Using statistical tools, they monitor production, evaluate system reliability, and guide engineering teams. The result: more efficient and consistent output.
Industrial / Quality Statistician
What They Do:
Industrial statisticians apply methods such as design of experiments, control charts, process capability analysis, and root-cause investigation. Their work supports continuous improvement, product testing, and quality assurance across a wide range of manufacturing environments.
Required Qualifications:
Most roles require a bachelor’s or master’s degree in statistics, industrial engineering, quality engineering, or a related technical field. Knowledge of Six Sigma methods, experimental design, and statistical process control is highly valued by employers.
Average Salary (US):
Industrial and quality statisticians usually earn between $75,000 and $115,000, depending on the industry and level of specialization.
Useful Notes:
This role is ideal for those who enjoy applied problem-solving and working in hands-on environments. Industrial statisticians frequently collaborate with engineers and production teams, making communication and practical reasoning essential skills.
10. Market Research Statistician
Market research statisticians help companies understand consumer behavior, brand performance, and market trends. They guide decisions about product development, advertising strategies, pricing, customer experience, and competitive positioning. They work closely with marketing teams, product managers, and business leaders.
Market Research Statistician
What They Do:
They design surveys and experiments, analyze consumer datasets, segment audiences, evaluate marketing performance, and identify factors that influence customer decisions. Their work supports marketing teams, product managers, and business leaders who rely on data to understand customer needs.
Required Qualifications:
Most positions require a bachelor’s or master’s degree in statistics, marketing analytics, mathematics, or a related field. Skills in experimental design, segmentation modeling, regression analysis, SQL, and tools like R or Python are often required.
Average Salary (US):
Market research statisticians typically earn between $60,000 and $95,000, depending on experience, industry, and technical specialization.
Useful Notes:
This role suits students who enjoy working with consumer data and translating findings into practical business insights. It also offers opportunities to work across a wide range of industries, including retail, advertising, technology, and media.
Skills and Competencies Required to Be a Statistician
While statisticians work in a variety of industries, many share several key skills. These are the skills that allow them to interpret data accurately, collaborate with teams, and solve complex problems. However, it isn't just technical skills they need; as you'll see, it's a combination of technical and soft skills that makes an effective statistician.
Technical Skills
Any statistician worth their salt will have a strong technical foundation. Generally, these skills are developed during their degrees or other educational and training programs. These are the skills that help them work efficiently with complex datasets, build reliable models, and produce insights.
Statistical Modeling
Statisticians must understand how to build, interpret, and evaluate models that explain data or make predictions. This includes linear and generalized linear models, as well as more advanced techniques, depending on the industry.
Programming and Statistical Software
Proficiency in tools such as R, Python, SAS, or SQL is essential for data manipulation, analysis, and visualization. These skills also support automation and reproducible research workflows.
Data Management and Cleaning
Real-world datasets are rarely clean. The ability to structure, validate, and transform data is critical for ensuring accurate results and reliable insights.
Mathematical Foundations
Skills in probability, calculus, linear algebra, and inference support rigorous analysis. These mathematical tools help statisticians evaluate uncertainty and understand the behavior of statistical methods.
Data Visualization
Statisticians often create charts, dashboards, and visual summaries to help others interpret complex results. Clear visual communication improves decision-making and makes findings more accessible.
Domain Knowledge
Understanding the industry or field you work in helps statisticians design better studies, select appropriate methods, and interpret results with context. Examples include healthcare, finance, engineering, or marketing.
Soft Skills
Statisticians need to communicate clearly, collaborate with diverse teams, and apply sound judgment. They can't just rely on their technical skills. These are the soft skills that make a good statistician in the real world and not just on paper.
Communication and Translation
Statisticians must explain methods and results in ways that non-technical audiences can understand. Clear communication ensures that insights lead to effective decisions.
Problem Solving
The ability to approach unfamiliar data challenges, identify appropriate methods, and adapt to evolving problems is essential for applied statistical work.
Collaboration
Statisticians regularly work with researchers, engineers, managers, clinicians, policy analysts, and other specialists. Teamwork allows statistical insights to be integrated into broader projects.
Critical Thinking
Evaluating assumptions, questioning data sources, and assessing model validity all require careful judgment. Strong critical thinking helps avoid misleading conclusions.
Attention to Detail
Small errors can have significant consequences in modeling and reporting. Precision is vital in every stage of statistical analysis.
Ethical Reasoning
Statisticians often work with sensitive information or data that influences public policy or corporate decisions. Ethical judgment ensures data is used responsibly and in compliance with standards.
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