> Markdown version of [/jobs/ext/3836291-data-scientist-remote-eligible](https://www.wearedevelopers.com/jobs/ext/3836291-data-scientist-remote-eligible). 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). --- # Data Scientist (Remote Eligible) - **Company:** Mathematica, Inc. - **Location:** Princeton, NJ, United States (Remote available) - **Experience:** Experienced - **Salary:** $78,000.0 - $100,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Big Data, Network Analysis, Clinical Data Repository, Cloud Computing, Computer Programming, Data Cleansing, R (Programming Language), Python (Programming Language), Machine Learning, Mathematica, Natural Language Processing, NumPy, Markdown, Standard Sql, Unstructured Data, Data Processing, Snowflake, Electronic Medical Records, Generative AI, Scikit Learn, Information Technology, Data Analytics, Software Version Control, Data Pipelines, Databricks, Programming Languages - **Published:** October 19, 2026 - **Apply:** https://diversityjobs.com/career/18682445/Data-Scientist-Remote-Eligible-New-Jersey-Princeton ## About the Role * Master's degree in a technical field such as statistics, econometrics, data science, data analytics, mathematics, operations research, computer science, and/or social science; equivalent years of experience can be substituted * Demonstrated interest and/or experience using data science and/or statistics to contribute to projects with a policy/social impact in academic and/or professional settings * Experience applying generative AI programmatically to extract insights from unstructured data, construct new features for analysis, or as a part of a larger systematic analysis * Experience executing causal, predictive, and descriptive data science and statistics techniques including regression modeling, machine learning algorithms, network analysis, or natural language processing * At least three years of experience performing data cleaning and analysis using programming languages such as R, Python, or Julia in the academic, extra-curricular, or professional environment * Experience increasing personal efficiency by incorporating AI into the code development process. * Ability and desire to work independently and take initiative as part of an interdisciplinary team that may be geographically dispersed. This includes being able to learn from resources such as academic articles, white papers, self-guided tutorials, and package documentation and willingness to constantly learn and contribute to knowledge sharing with team members * Experience with reproducible research principles, version control, interactive visualizations, and common packages/libraries for supporting data science work in R, Python, and/or Julia (e.g., tidyverse, data.table, R Shiny, R Markdown, pandas, polars, NumPy, scikit-learn, MLJ.jl, DataFrames.jl, and/or Makie.jl) * Desired but not required: production-quality machine learning applications, cloud computing environments (e.g. AWS), and algorithmic fairness and ethics ## Description Mathematica applies expertise at the intersection of data, methods, policy, and practice to improve well-being around the world. We collaborate closely with public- and private-sector partners to translate big questions into deep insights that improve programs, refine strategies, and enhance understanding. Our work yields actionable information to guide decisions in wide-ranging policy areas, from health, education, early childhood, and family support to nutrition, employment, disability, and international development. Mathematica, the creation and deployment of data-driven approaches to solve problems and answer important policy questions for clients. A Data Scientist owns data processing and analysis tasks and supports more senior level data science staff in implementing statistical, machine learning, generative AI, and other data science methods for use in research reports, internal systems, or client systems. Data Scientists will work on all aspects of the data science project life cycle, including understanding client needs, building data pipelines, monitoring data quality, developing documentation, creating visualizations, brainstorming modeling approaches, and implementing those models. Our data scientists underpin our company's core offerings in program improvement, policy assessment, and data science, which yield crucial evidence and information for policy and decision makers. This position will work remotely or flexibly in one of our office locations. The ideal candidate for this open Data Science position has a strong interest in applying their skills to healthcare and a strong statistical background in causal inference and supporting methodologies such as imputation, matching, weighting, regression, quasi-experimental methods, and synthetic-comparison methods, among others. In addition to the required technical skills below, our healthcare-focused data scientists strongly benefit from additional knowledge of SQL or Scala, experience with big data analysis platforms such as Databricks or Snowflake, and familiarity with healthcare datasets such as Medicare or Medicaid claims and enrollment data and electronic medical records. Example projects include: * Evaluate and monitor the impacts of an alternative payment model for primary care in terms of care quality, cost, and health outcomes for diverse beneficiaries, using claims from thousands of primary care practices across the country. Use the same data to predict future hospital costs and behavior. * Develop and evaluate a reproducible benchmarking pipeline to compare state healthcare spending against peer markets nationwide, harmonizing multi-source claims and Census data, applying statistical matching to select comparable regions, and normalizing spending through risk-adjusted regression models to support state rate-setting decisions. * Build and evaluate interpretable machine learning models to predict clinical care tiers from health assessment data, supporting state healthcare program's transition to a new assessment tool. Partner with subject-matter experts to engineer clinically meaningful features from raw assessment items and apply stratified sampling and diagnostics to deliver transparent models suited to high-stakes eligibility and reimbursement decisions Specifically, this Data Scientist contributes to team-based projects by: * Conducting causal, predictive, and descriptive analyses * Writing and maintaining programming systems in languages such as Python and R to build and evaluate models * Developing reliable data pipelines to obtain, combine, and transform datasets on cloud, internal, and client servers * Communicating technical results to diverse stakeholders including clients and cross-functional teams * Developing and maintaining technical and methodological documentation * Co-developing analysis plans with a senior data scientist or researcher * Leading and managing small teams and tasks with oversight from a more senior staff member