Statistician III

NORC at the University of Chicago•Chicago, IL

3d•Hybrid

About The Position

NORC at the University of Chicago is seeking a qualified Statistician III to join the Statistics and Data Science department. Statisticians in this role work cross-functionally across a diverse portfolio of projects in NORC’s substantive areas - health, society, economics, and global research - to generate trustworthy data and analytic insights. They apply mathematical statistics and survey methodology, including sampling, weighting, and variance estimation. Statisticians develop and apply robust solutions and reproducible workflows across the data lifecycle for data cleaning, integration of multiple data sources, transformation, harmonization, validation, and analysis. NORC statisticians also support the responsible release of data and findings by applying techniques to protect study participant confidentiality, such as statistical disclosure limitation and synthetic data. They design and develop dashboards and data visualizations that communicate effectively to a variety of audiences. The Statistician III also leverages machine learning and AI to enhance analytic efficiency and impact. Additional responsibilities include mentoring early-career staff, presenting results to clients and professional audiences, contributing to proposals and business development efforts, and supporting the delivery of high-quality technical products. Statisticians III are expected to work collaboratively in a team-oriented environment. Qualified applicants must be eligible to work in the U.S. We regret that we are unable to offer visa sponsorship for this position. This is a hybrid role based in either our Chicago Loop or downtown Washington, DC office, with a minimum of six days per month in the office. Remote work status may be considered for outstanding candidates.

Requirements

Master’s degree in statistics, mathematics, data science, computer science, computational social science, or a related field required; Ph.D. preferred.
4 years of experience in positions of increasing responsibility in statistics, analytics, survey research, or related field. Or Ph.D.
Experience in at least one of the following areas: demonstrated leadership in data visualization design, including expertise with tools such as R, Tableau, and Power BI for static and interactive visualizations; experience with data disclosure limitation and data privacy methods, including risk assessment and mitigation for public data releases; sampling, weighting, and variance estimation; and developing analytical pipelines and data workflows to support statistical analysis, data visualization, and AI/ML applications.
Strong foundation in mathematical statistics, including probability theory, statistical estimation, inference, modeling, and study design.
Proficiency in R and Python.
SAS proficiency is a plus.
Experience applying reproducible research and statistical programming best practices, including version control, code review, testing, documentation, and quality assurance.
Ability to organize and prioritize work to meet project needs.
Strong interpersonal and critical reasoning skills.
Proficiency with MS Office.

Responsibilities

Provide statistical expertise across projects, including study design and advanced methods; contribute to technical planning and help manage quality of work products from other staff.
Lead survey statistics tasks, including sample selection, weighting, nonresponse analyses, variance estimation; contribute to sample design and analysis sections of reports.
Develop robust data engineering and analytics pipelines to support reproducible, scalable analysis and ML/AI applications.
Uphold data disclosure limitation and data privacy best practices; apply statistical disclosure limitation for public releases and restricted-use data.
Create dashboards and data visualizations; design effective, stakeholder-ready visual products and set data visualization standards for projects.
Design and develop programs/scripts for data cleaning, integration, transformation, harmonization, and validation; create and maintain data documentation and dictionaries.
Write and implement SAS, R, and Python programs to extract/manipulate data, link complex datasets, and execute statistical and machine learning analyses.
Establish reproducible, quality‑assured analytic workflows; implement version control (Git), environment management, peer code review, automated testing, and validation checks.
Present results to clients and professional audiences; interact with clients to clarify needs, report progress, and provide recommendations.
Mentor early career staff on technical tasks and career development; contribute to proposals and business development activities.
Perform other duties as assigned.

Benefits

Generously subsidized health insurance, effective on the first day of employment
Dental and vision insurance
A defined contribution retirement program, along with a separate voluntary 403(b) retirement program
Group life insurance, long-term and short-term disability insurance
Generous paid time off
Holidays
Paid parental leave
Bereavement leave
Tuition assistance
An Employee Assistance Program (EAP)