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Data Scientist I - Computational Research, Statistics & Machine Learning

Pay
$90,000–100,000/yearAnnual period assumed — pay source
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:
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Work setting
Hybrid — work setting source
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: 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.
Read the full posting
Employment
Not stated

Before you apply

Work authorization
Must already have the right to work in the USQualified applicants must be eligible to work in the US We regret that we are unable to offer visa sponsorship for this position

What you’ll work on

Full posting
  • Build statistical and machine learning methods for survey and social science research

  • Build reproducible, quality-checked analytic workflows with Git and code review

  • Develop data pipelines that integrate structured and unstructured data

  • Design data products, dashboards, and applications for decision making

  • Deploy AI-enabled analytic applications using machine learning and NLP

From the employer’s posting
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
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.

What you’ll bring

All qualifications

Core experience

  • 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.

Preferred experience

  • Experience with large-scale data platforms such as Databricks, Spark, Hadoop, or Hive.
  • Experience analyzing healthcare, survey, administrative, or other large-scale observational datasets, especially healthcare claims data.
  • 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 with record linkage.
Qualification wording
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.
Experience with large-scale data platforms such as Databricks, Spark, Hadoop, or Hive.
Experience analyzing healthcare, survey, administrative, or other large-scale observational datasets, especially healthcare claims data.
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 with record linkage.
Education & alternatives
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.

About NORC at the University of Chicago

For over 80 years, NORC has evolved in many ways, moving the needle with research methods, technical applications and groundbreaking research findings.

In the employer’s words · Read in context

Posting record

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Actively hiringFirst seen by us 7 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 29, 20267 days ago
Recorded sightings
23
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

Lower than most similar jobs

$90K–$100K against $118K–$193K, the middle half of what similar US postings state.

From 3,721 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 7

Similar jobs usually come down between day 7 and day 56.

From 10,201 similar postings that came down. Coming down is not always a hire.

NORC at the University of Chicago is hiring

6 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • R
  • SAS
  • SQL
  • AWS
  • Azure
  • Databricks
  • GCP
  • Hadoop
  • Hive
  • Spark
Where the posting names them
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: 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.
- 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.
- 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 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.
- Demonstrated proficiency developing production-quality code in Python. - Strong experience with SQL and relational databases. - Experience developing software, data pipelines, or analytical applications.
- 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.
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).

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Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 1,411, the most 2,973, and the latest week had 1,826.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

Data Scientist I - Computational Research, Statistics & Machine Learning

Apply now 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: 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.

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

Please include a Resume and Cover Letter when applying. Candidates should be prepared to provide professional references upon request.

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.

#LI-MS1

   

 

Advertised: September 28, 2026 Central Daylight Time Applications close:

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Pay
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:
Location & working pattern

Chicago - 300 E Randolph St

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: 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.
Work authorization
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
More source context
- Experience with record linkage. Qualified applicants must be eligible to work in the U.S. We regret that we are unable to offer visa sponsorship for this position. Please include a Resume and Cover Letter when applying. Candidates should be prepared to provide professional references upon request.

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