> Markdown version of [/jobs/ext/2586143-statistician-researcher-ml-ai-applications-modeling](https://www.wearedevelopers.com/jobs/ext/2586143-statistician-researcher-ml-ai-applications-modeling). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Statistician Researcher - ML/AI applications/modeling - **Company:** National Opinion Research Center - NORC - **Location:** Washington, DC, United States (Remote available) - **Experience:** Experienced - **Salary:** $130,000.0 - $140,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Automation of Tests, Code Review, Data Cleansing, Information Engineering, Data Visualization, R (Programming Language), Python (Programming Language), Machine Learning, Microsoft Office, Power BI, SAS (Software), Tableau (Software), Git, Information Technology, Software Version Control - **Published:** August 6, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/87991265/1 ## About the Role * 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. ## Description 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., The Statistics and Data Science department implements state-of-the-art statistical methods and develops innovations to deliver reliable data and rigorous analyses that guide critical programmatic, business and policy decisions for NORC clients. The department provides leadership throughout the project lifecycle on study design, data collection, assessment of data quality, quantitative analysis, and dissemination of results. The Statistics and Data Science department also conducts its own research and is a leader in designing and implementing rigorous, efficient methods for sampling, weighting, and imputation for sample surveys and evaluation research. The department provides expertise and leads NORC strategy on the use of a broad range of methods and techniques, including statistical modeling, machine learning methods, data linkage, statistical matching, statistical disclosure limitation, small area estimation, Bayesian analysis, assessing data quality, data visualization for analyzing and interpreting data, and developing approaches using artificial intelligence (AI) that support NORC's research. The department collaborates with departments throughout NORC, as well as leading its own projects. 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, qualityassured 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. ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [Are Code Reviews Worth It? Insights from 16 Years of Review Data](https://www.wearedevelopers.com/videos/1135-are-code-reviews-worth-it-insights-from-16-years-of-review-data) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Build a CI/CD pipeline to automate code reviews and ensure code quality](https://www.wearedevelopers.com/videos/349-build-a-ci-cd-pipeline-to-automate-code-reviews-and-ensure-code-quality) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [How to start an AI project for a good cause and boost your career](https://www.wearedevelopers.com/magazine/15-how-to-start-an-ai-project-for-a-good-cause-and-boost-your-career)