Mid-Level Data Scientist- Hybrid (DMV Area) at Swingtech
Greenbelt, MD
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Jun 29, 2026
Greenbelt, MD
Jul 21, 2026
What this job asks for AI summary
This role supports a federal healthcare regulatory client by analyzing large healthcare datasets — including claims, assessment systems, and public health data — to drive compliance determinations and payment decisions under Medicare quality reporting programs. Day-to-day work involves building and maintaining analytic workflows, dashboards, and visualizations on AWS, writing Python, SQL, and PySpark, and communicating findings to non-technical stakeholders. It suits a data professional with healthcare industry experience and a background in cloud-based analytics environments.
Mid level · 3+ years · National · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $122,874 (middle half $87,544–$162,374).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (11)
No work location or metro area is specified in the posting; the role is at a federal healthcare regulatory client site, likely in the Washington DC area given the federal/CMS context, but this is not stated explicitly.
The posting says 'flexible work arrangements' but does not confirm fully remote work; remote is set to false as the role involves client-approved secure environments.
Degree requirement is set to None because the JD explicitly states 'additional experience may be considered in lieu of Master's degree,' making the degree substitutable.
The role title is 'Data Scientist' but the day-to-day work is heavily compliance analytics, dashboarding, and reporting — closer to operations research/data analysis than ML/modeling. 15-2051 is chosen as the primary code given the title and the presence of forecasting and feature engineering; 15-2031 is the runner-up given the compliance, trend analysis, and BI-heavy workload.
Clearance is set to None: the JD requires U.S. citizenship and the ability to obtain a federal public trust/suitability determination, which is not a security clearance.
Python and R are listed together as 'Python and/or R' in the qualifications section — emitted as one skill (Python) with R as an alternative.
Databricks, Spark, and PySpark are listed together ('Databricks, Spark, and/or PySpark') — emitted as PySpark (primary, most specific) with Spark as an alternative, and Databricks as a separate named platform since it is a distinct product.
Data visualization tools (QuickSight, Tableau, Power BI) are listed as interchangeable options under qualifications; QuickSight is also called out separately as a preferred experience — emitted as one required skill (Tableau as primary) with alternatives, plus a separate preferred skill for QuickSight specifically.
SharePoint, JIRA, and Confluence appear in the qualifications section and are treated as hard gates despite being collaboration/productivity tools.
Healthcare domain experience and claims data experience appear under qualifications but are framed with 'demonstrated experience' and 'strongly preferred' / 'preferred' language respectively — healthcare data analysis is marked required (demonstrated experience language) while claims data is marked preferred ('strongly preferred' but not a hard gate).
Ignored 2 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): healthcare data analysis, claims data analysis.
Read the full posting
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