Statisticians

Salary Overview

Job Outlook (2024–2034)

Key Skills

Knowledge Areas

What They Do

• Analyze and interpret statistical data to identify significant differences in relationships among sources of information.
• Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.
• Report results of statistical analyses, including information in the form of graphs, charts, and tables.
• Determine whether statistical methods are appropriate, based on user needs or research questions of interest.
• Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.
• Develop and test experimental designs, sampling techniques, and analytical methods.
• Identify relationships and trends in data, as well as any factors that could affect the results of research.
• Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients, peers, and students.

Tools & Technology

★ = Hot Technology (in-demand)

Education Requirements

Typical entry-level education: Master's Degree

Related Careers

Careers with the highest skill compatibility from Statisticians.

A Day in the Life

A statistician's day typically begins with reviewing the analytical questions and data available for current projects, designing or refining statistical models that will best address the research objectives at hand. Programming in R, Python, SAS, or other statistical computing environments occupies a substantial portion of the workday, as statisticians write, test, and debug code that implements their analytical approaches on real datasets. Collaboration with domain experts—physicians, engineers, economists, or marketing managers—is central to the work, as statisticians must deeply understand the substantive context of the problems they are analyzing to select appropriate methods and interpret results meaningfully. Preparing and presenting technical reports, visualizations, and briefings for both statistical peers and non-technical decision-makers is a regular deliverable that tests communication skills as much as analytical ones. Consulting on study design for upcoming data collection efforts is another key contribution, as statistical expertise at the design stage prevents the analytical problems that cannot be fixed after data has been collected.

Work Environment

Statisticians work in remarkably diverse settings including pharmaceutical companies, government agencies (Census Bureau, BLS, FDA, NIH), universities, financial institutions, technology companies, consulting firms, and non-profit research organizations. The work is primarily office-based and computer-intensive, with significant time spent in statistical programming environments and collaborative meetings with project teams. Academic statisticians divide time between research, teaching, and service, while industry statisticians focus almost entirely on applied analysis and collaboration with business or scientific partners. Remote work is increasingly prevalent in both industry and government statistics roles, with many teams distributed across multiple locations. The intellectual environment is collaborative and stimulating, as statisticians frequently engage with fascinating substantive problems in fields ranging far beyond statistics itself.

Career Path & Advancement

Statisticians typically enter the field with a graduate degree—a master's in statistics or biostatistics is sufficient for many industry and government positions, while a doctorate is generally required for academic faculty positions and senior research scientist roles at national laboratories and major research institutions. Undergraduate preparation in mathematics, statistics, computer science, or a quantitative social science provides the mathematical foundation for graduate study, with strong probability and linear algebra preparation being particularly important. Early career statisticians often specialize in a particular application domain—pharmaceutical biostatistics, economic research, social survey methodology, or environmental science—developing deep expertise in both the statistical methods and the substantive questions of their field. Senior statisticians assume leadership over entire analytical programs, mentoring junior colleagues, making methodology decisions for large studies, and contributing to the profession through publications and professional service. Fellow of the American Statistical Association (ASA) designation and elected positions in professional societies represent the highest professional recognition in the field.

Specializations

Biostatistics is one of the largest specializations, applying statistical methods to biological and health sciences data—clinical trials, epidemiology, genetics, and public health research—with rigorous regulatory standards governing pharmaceutical and medical device applications. Survey statistics focuses on the design and analysis of probability samples used in national surveys measuring unemployment, income, health outcomes, and population characteristics, requiring deep expertise in sampling theory and survey methodology. Mathematical statistics operates at the theoretical frontier of the discipline, developing new distributional theory, estimation methods, and hypothesis testing frameworks that advance the conceptual foundations of applied statistics. Data science and machine learning represents a rapidly growing adjacent area where statisticians apply predictive modeling, uncertainty quantification, and interpretability expertise that computational approaches alone often lack.

Pros & Cons

Industry Insight

The Bureau of Labor Statistics projects employment for statisticians to grow far faster than average, driven by the data revolution transforming business analytics, pharmaceutical development, technology, and government. The pharmaceutical and biotechnology sector is one of the largest employers of statisticians, with regulatory requirements for rigorous statistical analysis of clinical trial data creating consistent high-value demand for biostatisticians. Technology and internet companies compete vigorously for statistics and data science talent, offering among the highest compensation packages in the field and placing statisticians at the center of product development, advertising effectiveness, and platform recommendation systems. Artificial intelligence applications increasingly require statisticians to provide uncertainty quantification, model interpretability, and rigorous validation frameworks that distinguish reliable AI from overfitted noise. Compensation for experienced statisticians—particularly those with machine learning fluency—is among the highest of any scientific profession, reflecting strong employer competition for a relatively constrained talent pool.