INDEX ANALYTICS LLC

Senior Data Analyst / Researcher

INDEX ANALYTICS LLC Baltimore County, Maryland, United States · $120K–$155K/yr

IT Services and IT Consulting · 201-500 employees

Yesterday
Remote data-analyst Principal (10+ yrs) Other United States
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About the role

The Senior Data Analyst will conduct quantitative and qualitative research on Medicaid and CHIP data to provide actionable insights for federal healthcare programs. They will collaborate with cross-functional teams to develop predictive models, reports, and visualizations that support evidence-based decision-making and policy improvements.

What they look for

Data Analysis Statistical Methods Predictive Modeling Medicaid CHIP SQL PySpark Data Visualization Healthcare Policy Research Methodologies Agile Data Mining Regression Analysis Hypothesis Testing Program Evaluation Python

Requirements

Candidates must have a bachelor's degree and at least 10 years of professional experience, or an equivalent combination of education and experience. Proficiency in SQL, PySpark, or similar technologies and direct experience with Medicaid/CHIP data assets are required.

Full description

Job DetailsLevel: SeniorJob Location: Remote - Baltimore, MD 21244Education Level: 4 Year DegreeSalary Range: $120,000.00 - $155,000.00 Salary/year a { text-decoration: none; color: #464feb; } tr th, tr td { border: 1px solid #e6e6e6; } tr th { background-color: #f5f5f5; } Position Overview Index Analytics is seeking a Senior Data Analyst / Researcher to support federal healthcare clients by applying advanced analytical, statistical, and research methodologies to transform complex healthcare and program data into actionable insights. This role combines deep expertise in Medicaid and CHIP programs, data analytics, policy research, and stakeholder engagement to support evidence-based decision-making, program oversight, and healthcare transformation initiatives. The ideal candidate will be able to lead and conduct quantitative and qualitative analyses across diverse healthcare data sources, including claims, enrollment, utilization, quality, and performance datasets, to identify trends, evaluate program effectiveness, and inform policy and operational improvements. Working closely with data scientists, engineers, health policy researchers, and client stakeholders, this position develops high-impact analyses, predictive models, visualizations, and research products that support strategic priorities and improve outcomes for federal healthcare programs. Key Responsibilities Conduct research on best practices and analyze diverse Medicaid and Children’s Health Insurance Program (CHIP) data sources including claims, TAF, program oversight metrics, scorecards, and performance data to identify patterns, clusters, and insights that inform policy, operational improvements, and feature development for CMS business needs. Perform routine and exploratory data analysis using statistical methods, predictive modeling, and state‑of‑the‑art data mining techniques to build predictive models, uncover trends, and generate actionable insights. Develop and deliver high‑quality reports, ad hoc analyses, and data visualizations grounded in HCD and UX best practices to help clients interpret complex information and support decision‑making. Work collaboratively in an agile environment with data analysts, data scientists, and internal/external clients to define analytical requirements, develop value‑added solutions, and enhance business operations. Prepare technical deliverables including presentation decks, reports, and draft manuscripts communicating findings to clients and scientific audiences through clear, compelling presentations that translate complex concepts for diverse stakeholders. Integrate qualitative design research with exploratory data analysis to provide insights that support improved health policy and better outcomes for Medicaid and CHIP populations. Use analytics and data expertise to provide input to and review of documentation, reference, and training materials related to analytic approaches, data structures and content, and data quality observations. Qualifications a { text-decoration: none; color: #464feb; } tr th, tr td { border: 1px solid #e6e6e6; } tr th { background-color: #f5f5f5; } U.S. Citizen or otherwise authorized to work in the United States and able to demonstrate physical residency in the U.S. for at least three of the past five years. Must be eligible to support federal government clients and meet applicable background investigation requirements. Bachelor's degree and a minimum of 10 years of professional experience, or an equivalent combination of education and experience. Four years of specialized experience may be substituted for a bachelor's degree. Candidates should possess significant experience supporting data analytics, business intelligence, research, or related healthcare and government initiatives. Demonstrated experience applying statistical methods and analytical techniques, including probability distributions, hypothesis testing, regression analysis, predictive modeling, data mining, and advanced data visualization to support data-driven decision-making, program administration, policy development, and program oversight. Strong experience conducting complex quantitative and qualitative analyses using large healthcare datasets to evaluate program performance, identify trends, measure outcomes, and support operational and policy improvements. Hands-on experience performing data analytics using SQL, PySpark, or comparable technologies is required. Direct experience working with Medicaid and CHIP data assets, including T-MSIS Analytic Files (TAF), CMS-416T reports, state performance measures, and health outcomes reporting, is required. Experience with DQ Atlas, Scorecard, or related CMS performance monitoring tools is preferred. Experience developing reports, dashboards, data visualizations, and analytical products that effectively communicate findings to technical, business, and executive audiences. Subject matter expertise in text analytics is preferred. Experience applying Natural Language Processing (NLP) techniques using Python or similar technologies is a plus. Proficiency with Python, R, or other analytical programming languages is preferred. Knowledge of healthcare policy, Medicaid and CHIP programs, population health, quality measurement, program evaluation, or healthcare performance improvement initiatives is highly desirable. Experience supporting the Centers for Medicare & Medicaid Services (CMS) or other federal, state, or local government agencies is preferred. Strong written, verbal, and presentation communication skills, with demonstrated ability to translate complex analytical findings into actionable recommendations for diverse stakeholder groups. Proven ability to work collaboratively within cross-functional teams, manage multiple priorities, and support client-facing engagements in an Agile or fast-paced project environment.

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