Data Scientist I - Computational Research, Statistics & Machine Learning
Chicago - 300 E Randolph St
- 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:
Read the full posting- 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
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
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
What you’ll work on
Full postingBuild 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 qualificationsCore 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.
Tools in this posting
- Python
- R
- SAS
- SQL
- AWS
- Azure
- Databricks
- GCP
- Hadoop
- Hive
- Spark
Source — Tool mentions in context
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).
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
Report an errorActively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 29, 2026 · 1 day ago
- Recorded sightings
- 17
- Last seen by us
- Oct 30, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
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
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.
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.
- 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.
- 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.
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.
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Advertised: September 28, 2026 Central Daylight Time Applications close:
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- 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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