Mid-Level Data Scientist- Hybrid (DMV Area)

Swingtech•Greenbelt, MD

5d•Hybrid

About The Position

The Data Scientist will support a federal healthcare regulatory client responsible for national healthcare quality reporting programs across post-acute care settings. This role focuses on compliance analytics, payment determination support, public reporting, and monitoring and evaluation activities for healthcare providers operating under federally mandated Medicare quality reporting requirements. The Data Scientist will work closely with client stakeholders, program analysts, and technical teams to analyze complex healthcare datasets, develop analytic workflows and dashboards, and support data-driven decision-making. All work is performed within client-approved secure environments in accordance with federal data security and privacy requirements.

Requirements

Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Public Health, Health Informatics, or a related field (additional experience may be considered in lieu of Master’s degree).
Minimum of 3+ years of experience analyzing large, complex datasets from multiple sources.
Strong experience with SQL and relational database management.
Experience working within cloud-based analytics environments, preferably AWS or equivalent.
Hands-on experience with Databricks, Spark, and/or PySpark.
Experience with data visualization tools such as cloud-based BI platforms such as QuickSight, Tableau, Power BI, or similar.
Experience using Python and/or R for data analysis and modeling.
Familiarity with modernizing analytics platforms, including transitioning from legacy analytic solutions to open-source technologies.
Experience using MS Office Suite tools with advanced experience in Excel.
Experience using MS SharePoint and MS Office Suite as well as Atlassian JIRA and Confluence.
Demonstrated experience in the healthcare industry, particularly healthcare quality measurement, outcomes research, or health services research.
Strong written and verbal communication skills, with the ability to translate complex analytic findings into clear, actionable insights for non-technical stakeholders.
Ability to work in a fast-paced, deadline-driven environment while managing multiple priorities.
Must be a U.S. Citizen
Ability to obtain and maintain required federal suitability or public trust, as applicable

Nice To Haves

Preferred experience with AWS QuickSight.
Experience analyzing provider level claims data, survey data, patient-level data, or quality reporting datasets strongly preferred.
Experience supporting federal healthcare programs, regulatory initiatives, or large-scale compliance programs preferred.

Responsibilities

Analyzing large, complex healthcare datasets to support provider compliance determinations to support annual payment update decision-making.
Performing data cleaning, preprocessing, validation, reconciliation, and forecasting using multiple healthcare data sources. feature engineering across multiple healthcare data sources.
Integrating and analyzing data from standardized assessment systems, administrative claims, public health surveillance data, CDC data, and other approved external data sources.
Developing, maintaining, and enhancing analytic workflows, dashboards, and reports within client-approved centralized analytics AWS platforms.
As needed, refactoring legacy code into Python, SQL, or PySpark in alignment with federal data modernization initiatives.
Producing quarterly and annual compliance analytics, including identification of non-compliant providers and generation of program-level compliance lists.
Supporting monitoring and evaluation activities, including trend analysis, performance measurement, and year-over-year comparisons.
Creating data visualizations and analytic summaries using tools such as cloud-based BI platforms and big data analytics tools to communicate findings to client stakeholders.
Review data dictionaries to support updates to Source to Target Mappings and create or implement associated change requests.
Support ad hoc data analyses to inform policy decisions, regulatory updates, and program improvements.
Documenting analytic methodologies, business rules, data sources, and processes in accordance with federal documentation and accessibility standards.
Collaborating with cross-functional teams using agile project management and collaboration tools to manage requirements, track work, and support timely delivery.