Data Scientist

DUTIES: Analyze, manipulate, or process large sets of data using statistical software. Clean and manipulate raw data using statistical software. Identify business problems or management objectives that can be addressed through data analysis. Recommend data-driven solutions to key stakeholders. Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software. Execute end-to-end analyses to answer key product and business questions. Apply SQL and analytical programming tools to extract, transform, and analyze data from various data sources with accuracy and reproducibility. Design and analyze experiments using valid frameworks, correctly interpreting results and surfacing limitations, assumptions, and sources of uncertainty. Perform structured investigations into metric changes and evaluate plausible drivers. Partner with Product, Engineering, and Data Engineering to validate metric definitions, experiment setup, and measurement readiness. Clearly document analytical context, methodology, assumptions, and conclusions to ensure work can be understood and reused by others. Communicate findings to stakeholders in a clear and concise manner, focusing on how results answer the underlying business question. Identify potential data quality or measurement issues and escalate them appropriately. Design causal analyses for complex initiatives, ensuring methodological soundness and appropriate interpretation of results. Remote work may be permitted on occasion within a commutable distance from the worksite. REQUIREMENTS: Bachelor’s degree or foreign equivalent in Business Analytics, Engineering (any), Math or related; and 2 years of experience in the job offered or a related quantitative occupation. Must include 2 years of experience in each of the following: Reviewing business intelligence, dashboarding, reporting, and data analytics using Tableau, Looker, BigQuery, and AWS (S3) to monitor key metrics, analyze trends, and deliver insights that support process execution, financial analysis, and product development; Analyzing statistical modeling, causal analytics, and experimental design using R (including R Shiny) and SQL to implement clear, actionable insights that inform product strategy, optimize financial outcomes, and guide data-driven business decisions; Manipulating large data sets using Python and Snowflake to perform data extraction, cleaning, transformation, and workflow automation for reporting and analysis; Using Tableau, Looker, and visualization tools including Figma, FigJam, and Miro to translate complex analyses into dashboards, reports, and visual insights that communicate results, identify opportunities, and provide recommendations to stakeholders across product, finance, and business teams. OTHER: Job Site: New York, NY; 40 hours/week; Salary: $165,000 – $175,000 per year.

Fixing healthcare starts with fixing access to it. And we're still just getting started. DUTIES: Analyze, manipulate, or process large sets of data using statistical software. Clean and manipulate raw data using statistical software. Identify business problems or management objectives that can be addressed through data analysis. Recommend data-driven solutions to key stakeholders. Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software. Execute end-to-end analyses to answer key product and business questions. Apply SQL and analytical programming tools to extract, transform, and analyze data from various data sources with accuracy and reproducibility. Design and analyze experiments using valid frameworks, correctly interpreting results and surfacing limitations, assumptions, and sources of uncertainty. Perform structured investigations into metric changes and evaluate plausible drivers. Partner with Product, Engineering, and Data Engineering to validate metric definitions, experiment setup, and measurement readiness. Clearly document analytical context, methodology, assumptions, and conclusions to ensure work can be understood and reused by others. Communicate findings to stakeholders in a clear and concise manner, focusing on how results answer the underlying business question. Identify potential data quality or measurement issues and escalate them appropriately. Design causal analyses for complex initiatives, ensuring methodological soundness and appropriate interpretation of results. Remote work may be permitted on occasion within a commutable distance from the worksite. REQUIREMENTS: Bachelor’s degree or foreign equivalent in Business Analytics, Engineering (any), Math or related; and 2 years of experience in the job offered or a related quantitative occupation. Must include 2 years of experience in each of the following: Reviewing business intelligence, dashboarding, reporting, and data analytics using Tableau, Looker, BigQuery, and AWS (S3) to monitor key metrics, analyze trends, and deliver insights that support process execution, financial analysis, and product development; Analyzing statistical modeling, causal analytics, and experimental design using R (including R Shiny) and SQL to implement clear, actionable insights that inform product strategy, optimize financial outcomes, and guide data-driven business decisions; Manipulating large data sets using Python and Snowflake to perform data extraction, cleaning, transformation, and workflow automation for reporting and analysis; Using Tableau, Looker, and visualization tools including Figma, FigJam, and Miro to translate complex analyses into dashboards, reports, and visual insights that communicate results, identify opportunities, and provide recommendations to stakeholders across product, finance, and business teams.