Statistician
SOC 15-2041.00 · ESCO 2120 · OSCA 223133
Role snapshot
Overview
Designs experiments and surveys, builds mathematical models, and analyses numerical data to uncover trends and inform decisions across fields like medicine, government, and business. Statisticians apply rigorous quantitative methods to collect, process, and interpret complex data sets, providing critical insights that drive strategic planning and evidence-based policy.
Provides objective, data-driven insights that are crucial for scientific discovery, policy making, business strategy, and product development, directly influencing outcomes in public health, economics, and technology.
On the job
- Develop and implement statistical models for data analysis and prediction.
- Design and oversee data collection methods, including surveys, experiments, and observational studies.
- Interpret complex statistical results and communicate findings to non-technical stakeholders through reports and presentations.
- Advise on data-driven decision-making and provide recommendations based on analytical insights.
- Clean, process, and validate large datasets to ensure accuracy and reliability for analysis.
Tools & technology
Average salary
Job outlook
ExcellentNew job opportunities are highly likely. Demand significantly outpaces supply in most markets.
Education & training
A master's or PhD degree in statistics, mathematics, data science, or a related quantitative field is typically required.
AI impact outlook
Note — this is our current view. AI is moving fast, so we revisit these ratings.
Show how this was assessed Hide the detail
Note — this is our current view. AI is moving fast, so we revisit these ratings.
Show how this was assessed Hide the detailWhy this role received this rating
Core task exposure
high
How much of the role’s important work could AI perform?
Developing and implementing statistical models, interpreting initial results, and data cleaning are core tasks increasingly exposed to AI.
End-to-end automation
moderate
Can AI complete the work without substantial human involvement?
While AI can generate models and reports, the rigorous evaluation of assumptions and critical advisory role require human expertise.
Adoption pressure
high
How likely are employers to introduce AI into this work?
Many sectors rely heavily on statistical insights, creating high pressure to automate routine analysis and speed up research.
Human dependence
moderate
How much does success depend on human judgement, relationships and accountability?
Success depends on deep theoretical understanding, ethical experimental design, and communicating nuanced findings for critical, often sensitive, decisions.
Protective — a higher rating lowers the overall score.
Role adaptability
strong
How easily can the role evolve as AI takes on more tasks?
The foundational mathematical and statistical skills are highly versatile, allowing statisticians to adapt to various industries and analytical challenges.
Shown for context — not part of the score.
What AI may take on
These are the parts of the role most likely to be automated or significantly accelerated.
- Develop and implement standard statistical models for data analysis
- Clean, process, and validate large datasets to ensure accuracy
- Interpret initial complex statistical results and identify trends
- Automate generation of reports and presentations on findings
Where people remain essential
These parts continue to depend heavily on human judgement, relationships and accountability.
- Design and oversee complex, ethical data collection methods and experiments
- Interpret nuanced statistical findings and their real-world implications
- Advise on data-driven decision-making and provide strategic recommendations
- Communicate complex insights to non-technical stakeholders persuasively
- Validate model assumptions and limitations, especially in novel contexts
- Develop novel statistical methodologies for emerging problems
How the role may evolve
Shifting focus from data crunching to deep methodological oversight and ethical guidance.
The statistician's role will move from executing calculations and basic modeling to ensuring the validity, ethics, and appropriate application of AI-driven statistical tools, becoming more of a methodological expert and advisor.
Strengthen your future fit
- Deep theoretical understanding of statistical methods
- Expertise in AI/ML model interpretation and robustness
- Ethical considerations in data science and AI
- Advanced communication for technical and non-technical audiences
- Consulting and advisory skills
- Assessment horizon
- 3–7 years
- Confidence
- Medium
- Last reviewed
- August 2026
- Methodology
- v1.0
This assessment reflects current AI capabilities and expected adoption patterns. Actual impacts will vary by industry, employer and the way each role is performed.
Career pathways
WHERE YOU COULD GO
CURRENT ROLE
Statistician
Data & AI
ADJACENT MOVES
STARTING POINTS
Who thrives here
Interest profile
investigative · ICR
Individuals who enjoy systematic investigation, applying logical reasoning to complex problems, and working with data and precise methods often excel in this role.
Personality characteristics
Curious
Possesses a strong desire to understand underlying mechanisms and explore data for new insights.
Methodical
Applies systematic and logical approaches to problem-solving and experimental design, ensuring rigor.
Detail-oriented
Pays close attention to the nuances of data, statistical assumptions, and model specifications to ensure accuracy.
Objective
Maintains impartiality when interpreting data, ensuring conclusions are based on evidence, not personal bias.
Reserved
Prefers working independently or in small teams, focusing on analytical tasks rather than extensive social interaction.
Resilient
Handles the challenges of complex data, ambiguous problems, and critical review of methods without becoming easily discouraged.
Best for
- People who enjoy deep analytical thinking and quantitative problem-solving.
- Those who are motivated by uncovering patterns and making sense of complex, often ambiguous, data.
- Professionals who thrive in roles that require a blend of mathematical rigor and practical application to real-world issues.
Watch out for
- Requires a high degree of precision and attention to detail, which can be demanding and require sustained focus.
- May involve communicating complex technical concepts to non-technical audiences, which requires strong translation skills.
A week in the life
A representative working week for a Statistician — where the deep work, meetings, and admin actually land.
Real people. Real results.
Thousands of people
can't be wrong.
Frequently asked questions about Statistician roles
What does a Statistician do?
A Statistician designs experiments and surveys, builds mathematical models, and analyses numerical data to uncover trends and inform decisions across fields like medicine, government, and business. Statisticians apply rigorous quantitative methods to collect, process, and interpret complex data sets, providing critical insights that drive strategic planning and evidence-based policy. Provides objective, data-driven insights that are crucial for scientific discovery, policy making, business strategy, and product development, directly influencing outcomes in public health, economics, and technology.
How much does a Statistician earn?
A Statistician earns a median of $105,000 per year in the US, typically ranging from $75,000 to $140,000.
What qualifications do you need to become a Statistician?
To become a Statistician, a master's or PhD degree in statistics, mathematics, data science, or a related quantitative field is typically required.
What personality suits a Statistician?
Statistician roles tend to suit people who are highly conscientious — precise, organised and strong on follow-through (Conscientiousness 85/100) and open and curious — drawn to variety, ideas and new approaches (Openness 85/100). The traits that matter most in the role are Curious, Methodical, Detail-oriented and Objective. Possesses a strong desire to understand underlying mechanisms and explore data for new insights. On interests, Statistician maps to an ICR Holland Code profile — individuals who enjoy systematic investigation, applying logical reasoning to complex problems, and working with data and precise methods often excel in this role.
Who does a Statistician role suit?
A Statistician role is usually a strong fit for these reasons. Strong Investigative and Conventional alignment: the role demands rigorous analysis, systematic problem-solving, and precision. High focus on deep analytical work, model building, and data interpretation provides intellectual stimulation. Opportunity to influence key decisions with objective, data-driven insights across diverse fields.
What are the downsides of being a Statistician?
Statistician roles come with trade-offs worth weighing up. Requires a high degree of precision and attention to detail, which can be demanding and require sustained focus. May involve communicating complex technical concepts to non-technical audiences, which requires strong translation skills.
What is the work environment like for a Statistician?
Work as a Statistician is mostly office-based with hybrid arrangements common, semi-structured — a mix of set processes and self-directed work, a moderate pace and high exposure to clients or stakeholders. Around 61% of the week is focused deep work.
What skills do you need to be a Statistician?
Core skills for a Statistician include Statistical modeling, Experimental design, Data analysis and interpretation, Programming (R, Python, SAS), Data visualization and Communication of complex findings.
How do you become a Statistician?
Common entry routes into Statistician roles include Junior Statistician, Data Analyst and Research Assistant.
What career progression is there for a Statistician?
From a Statistician role, common next steps include Senior Statistician, Principal Statistician and Director of Analytics; lateral moves include Data Scientist and Quantitative Researcher.
What is the job outlook for Statistician roles?
The outlook for Statistician roles is currently rated excellent. New job opportunities are highly likely. Demand significantly outpaces supply in most markets.
Will AI replace Statistician roles?
Traitstack rates automation risk for Statistician roles at 61 out of 100, which is strong. Interpreting nuanced statistical results and advising on complex data-driven decisions will remain human-led, even as AI handles much of the model building and data processing. AI is most likely to take on develop and implement standard statistical models for data analysis, clean, process, and validate large datasets to ensure accuracy and interpret initial complex statistical results and identify trends. Design and oversee complex, ethical data collection methods and experiments, interpret nuanced statistical findings and their real-world implications and advise on data-driven decision-making and provide strategic recommendations stay with people. Shifting focus from data crunching to deep methodological oversight and ethical guidance. That score measures how much of the work could change, not the likelihood the job disappears. It is Traitstack's current view, revisited as AI capability moves.