Data Scientist I - Computational Research, Statistics & Machine Learning

NORC at the University of Chicago; Chicago (IL); On-site; USD 90,000 - 100,000; Full time

Benefits offered by this job

Health insurance

Dental and vision insurance

Retirement plan

Paid time off

Job summary

NORC at the University of Chicago is hiring a Data Scientist I in the Statistics and Data Science department in Chicago. You will develop statistical and machine learning solutions, manage data pipelines, and collaborate with researchers and software developers to improve research outcomes.

The role emphasizes reproducible workflows, Python expertise, SQL proficiency, and the application of AI methods to social science data.

Qualifications

• Bachelor's degree in computational social science, data science, statistics, computer science or related quantitative field.
• 4 years of relevant experience including graduate research, internships, and applied professional experience.
• Proficiency developing production-quality code in Python and SQL.

Responsibilities

• Apply statistical, computational, and machine learning methods to support survey research and social science studies.
• Establish reproducible analytic workflows with Git, environment management, testing, and validation.
• Develop robust data pipelines from structured and unstructured sources for research and operations.
• Design data products, dashboards, and automated tools for data‑driven decisions.
• Collaborate with multidisciplinary teams to deploy AI-enabled analytic applications.

Skills

Python programming

SQL

Git

Machine learning

Data management

Communication

Education

Bachelor's degree in quantitative field

Tools

Cloud platforms

Databricks/Spark/Hadoop

R

Job description

Data Scientist I - Computational Research, Statistics & Machine Learning

Job no: 503995 Work type: Regular Full-Time Location: Chicago - 300 E Randolph St Capability Area: Statistics and Data Science

JOB SUMMARY:

NORC at the University of Chicago is seeking a qualified Data Scientist to join the Statistics and Data Science department and support a diverse range of research projects.

The Data Scientist I works collaboratively with statisticians, researchers, methodologists, software developers, and subject matter experts to develop statistical, data science, and computational solutions that improve research, operational efficiency, and decision-making. This role combines strong foundations in data management, statistical modeling, machine learning, and computational social science. The position also provides opportunities to apply emerging technologies, including generative AI and large language models (LLMs), to research problems.

The Data Scientist I will contribute to projects involving structured and unstructured data, survey data, administrative records, commercial data, text data, and other novel data sources. Responsibilities may include developing analytical workflows, building statistical and machine learning models, creating data products and applications, and evaluating AI approaches for research and operational use.

The ideal candidate possesses strong Python programming skills, experience building reproducible analytical workflows, and an interest in applying advanced computational, statistical, and AI methods to solve complex research and business problems.

Location

Location: This is a hybrid role based in either our Chicago Loop or downtown DC office, with a minimum of six days per month in the office.

Qualified applicants must be eligible to work in the U.S. We regret that we are unable to offer visa sponsorship for this position.

DEPARTMENT: Statistics and Data Science

The Statistics and Data Science department implements state‑of‑the‑art statistical methods and develops innovations to deliver reliable data and rigorous analysis to 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, data disclosure control, 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 the departments throughout NORC, as well as leading its own projects.

RESPONSIBILITIES:

• Apply statistical, computational, and machine learning methods to support survey research, evaluation studies, and other social science research initiatives
• Establish reproducible, quality‑assured analytic workflows; implement version control (Git), environment management, peer code review, automated testing, and validation checks.
• Develop robust data pipelines that integrate, transform, and analyze structured and unstructured data from multiple sources to support research and operational objectives.
• Design and implement data products, dashboards, applications, and automated tools that enable data‑driven decision making.
• Apply machine learning, AI, and natural language processing methods and collaborate with multidisciplinary teams to design, evaluate, and deploy AI‑enabled analytic applications.
• Write and implement R, and Python programs to extract/manipulate data, link complex datasets, and execute statistical and machine learning analyses.
• Work with relational databases, cloud platforms, and large‑scale computing environments to manage and analyze complex datasets efficiently.
• Uphold data disclosure limitation and data privacy best practices; apply statistical disclosure limitation for public releases and restricted‑use data.
• Perform other duties as assigned.

REQUIRED SKILLS:

• Bachelor's degree in computational social science, data science, statistics, computer science or a related quantitative field.
• 4 years of relevant experience including graduate research, internships, and applied professional experience.
• Demonstrated proficiency developing production‑quality code in Python.
• Strong experience with SQL and relational databases.
• Experience developing software, data pipelines, or analytical applications.
• Experience conducting statistical analysis and machine learning using real‑world datasets.
• Knowledge of supervised and unsupervised machine learning methods.
• Experience working with Git and collaborative development workflows.
• Strong problem‑solving and analytical skills.
• Excellent communication and technical writing skills.
• Ability to explain technical concepts to diverse audiences.

Preferred Skills:

• Experience with large-scale data platforms such as Databricks, Spark, Hadoop, or Hive.
• Experience developing, evaluating, or deploying machine learning and AI solutions, including work with large language models, and cloud environments (e.g., AWS, Azure, GCP).
• Experience applying data disclosure limitation (SDL) and data privacy methods, including risk assessment and mitigation for public data releases.
• Experience with R or SAS
• Experience analyzing healthcare, survey, administrative, or other large‑scale observational datasets, especially healthcare claims data.
• Experience with record linkage.

SALARY AND BENEFITS:

The pay range for this position is $90,000-$100,000.

This position is classified as regular. Regular staff are eligible for NORC’s comprehensive benefits program. Benefits include, but are not limited to:

• 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
• Benefits that promote work/life balance, including generous paid time off, holidays; paid parental leave, bereavement leave, tuition assistance, and an Employee Assistance Program (EAP).

NORC is committed to equity and transparency in its pay practices. We publish salary ranges and benefit information for every job. The listed hiring range reflects what we, in good faith, expect to pay at the time of posting, though actual compensation may vary and may be adjusted over time. A candidate’s placement within the range depends on factors such as competencies, education, qualifications, experience, skills, performance, and organizational needs.

WHAT WE DO:

NORC at the University of Chicago is an objective, non-partisan research institution that delivers reliable data and rigorous analysis to guide critical programmatic, business, and policy decisions. Since 1941, our teams have conducted groundbreaking studies, created and applied innovative methods and tools, and advanced principles of scientific integrity and collaboration. Today, government, corporate, and nonprofit clients around the world partner with us to transform increasingly complex information into useful knowledge.

WHO WE ARE:

For over 80 years, NORC has evolved in many ways, moving the needle with research methods, technical applications and groundbreaking research findings. But our tradition of excellence, passion for innovation, and commitment to collegiality have remained constant components of who we are as a brand, and who each of us is as a member of the NORC team. With world‑class benefits, a business casual environment, and an emphasis on continuous learning, NORC is a place where people join for the stellar research and analysis work for which we’re known, and stay for the relationships they form with their colleagues who take pride in the impact their work is making on a global scale.

EEO STATEMENT:

NORC is an equal opportunity employer. NORC evaluates qualified applicants without regard to race, color, religion, sex, gender, national origin, disability, status as a protected veteran, sexual orientation, and other legally protected characteristics.