Data Scientist I: AI & ML for Social Science Research

NORC at the University of Chicago; Chicago (IL); Hybrid; 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

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.