Healthcare Claims Data Analyst

Type of Requisition:
Regular
Clearance Level Must Currently Possess:
None
Clearance Level Must Be Able to Obtain:
None Public Trust/Other Required:
None
Job Family:
Data Science and Data Engineering Job Qualifications:
Skills:
Data Analytics, Health Care, Python for Data Analysis, Statistical Analysis Certifications:
None Experience:
4 + years of related experience US Citizenship Required:
No
Job Description:

At GDIT, people are our differentiator. Our work depends on a Data Analyst joining our team to support Centers for Medicare and Medicaid Services anti-fraud activities.

As a Data Analyst supporting the Healthcare Fraud Prevention Partnership (HFPP), you will develop fraud, waste and abuse (FWA) analytics from concept to finished product at the Trusted Third Party (TTP), working against a multi-billion record claims warehouse assembled from dozens of public and private healthcare payers. HFPP Partners and the client bring the questions. You turn them into analytics that identify aberrant billing and hold up to scrutiny. You will engage with healthcare claims and FWA analytics working alongside experienced Subject Matter Experts, and you do need to be genuinely strong with data.

***W ork visa sponsorship will not be provided for this position. This is a remote role. Candidates must reside in the United States.

HOW A HEALTHCARE CLAIMS DATA ANALYST WILL MAKE AN IMPACT:

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Working with a multi-disciplinary team of Data Scientists, Business Intelligence Developers and FWA Subject Matter Experts. Our team is 100% remote and distributed throughout the country.

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Translating Partner and client requests into specifiable analytic questions, including determining what can and cannot be answered with the data available and raising that early rather than late.

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Developing FWA analytics end to end, building the analytic logic in SQL and Python against billions of claim records, testing it, and refining it in collaboration with FWA Subject Matter Experts until it identifies something real.

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Separating genuine aberrancy from patterns fully explained by legitimate clinical practice, coverage policy or claim edits, recognizing that the mundane explanation is usually the correct one and that finding it before a Partner does is part of the work.

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Documenting methodology, assumptions and data lineage so that each analytic can be reproduced and incorporated into the TTP analytic suite by another team without the original analyst present.

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Documenting findings and present results to internal stakeholders, and will participate in Partner discussions to clarify analytic requirements.

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Managing several concurrent requests against firm deadlines within a queue driven by Partner and client demand.

WHAT YOU'LL NEED TO SUCCEED:

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Bachelor's degree in a quantitative or health-related field, or equivalent hands-on experience.

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4+ years writing SQL against large relational data, including CTEs, window functions and multi-table joins at scale, with enough performance awareness to understand why a query is slow.

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Working proficiency in Python for data analysis, producing clean and reproducible analysis code (pandas or equivalent).

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Demonstrated ability to turn an ambiguous request into a defined analytic question, including recognizing when a question cannot be answered with the data at hand.

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Experience documenting analytic work such that another person can reproduce it, and evidence of having come up to speed quickly in an unfamiliar data domain.

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Ability to explain analytic results clearly, in writing and in conversation, to audiences who are not analysts.

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Accuracy, attention to detail and the organizational discipline to carry several concurrent requests without dropping any.

- US citizen or Permanent Resident

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Must be able to obtain/maintain Public Trust

DESIRED QUALIFICATIONS:

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Experience with healthcare claims data (Medicare, Medicaid or commercial) and healthcare coding systems (e.g