Healthcare Data Analyst

Type of Requisition:

Regular

Clearance Level Must Currently Possess:

None

Clearance Level Must Be Able to Obtain:

None

Public Trust/Other Required:

NACI (T1)

Job Family:

Data Science and Data Engineering

Job Qualifications:

Skills:

Agentic AI, Big Data, Generative AI, Machine Learning Methods, Python (Programming Language)

Certifications:

None

Experience:

5 + years of related experience

US Citizenship Required:

No

Job Description:

We are GDIT. We take pride in providing our clients with the data they need to make important decisions that impact the world around us.

You make GDIT your place by delivering insights to help our clients make impactful changes real. By owning your opportunity at GDIT, you’ll become a critical part in how we successfully solve our clients’ biggest challenges.

Our work is looking for a Sr. Data Scientist with deep experience in advanced analytics and modern AI technologies. In this role, you will help evolve the analytical capabilities used to detect and prevent fraud, waste, and abuse (FWA) in the Medicare and Medicaid programs. This includes working with cutting-edge generative AI models, AI agents, and scalable data science tools. A typical day will include:

• Analyzing Medicare and Medicaid claims data using statistical and machine learning techniques.
• Developing generative AI–powered solutions and agent-based systems to enhance fraud detection, investigate complex patterns, and optimize business processes.
• Building predictive and anomaly detection models to improve insights, efficiencies, and program integrity outcomes.
• Identifying opportunities to leverage large-scale CMS data with modern AI/ML methods, including LLMs, embeddings, vector databases, and retrieval-augmented pipelines.
• Present findings to a range of audiences (technical/non-technical) and to various levels of leadership.
• Performs additional duties as assigned.

Required Skills:

• Bachelors degree with an analytical or technical focus (i.e., Statistics, Computer Engineering, Applied Mathematics) or related area
• Minimum 5 years of experience in Data Science
• Minimum of 2 years of experience conducting advanced analyses of Medicare and/or Medicaid data
• Familiarity with R or Python for data science (including machine learning)
• Familiarity and experience with one or more of the following data science packages: Pandas, NumPy, Tensorflow, Scikit learn, Seaborn, GGplot, Matplotlib
• Familiarity with SQL, Databricks, Snowflake and Spark languages/technologies
• Hands-on experience with generative AI technologies such as LangChain, LangGraph, Hugging Face Transformers, vector databases, agent frameworks, or LLM orchestration tools.
• Understanding of statistics and basic analytic model development principles such as feature engineering, attribute selection, threshold setting, train/test split, etc.
• Ability to create data visualizations to present complex analyses and to illustrate trends
• A self-starter mindset with strong curiosity, problem‑solving abilities, and the ability to simplify and explain complex data and AI systems

  The likely salary range for this position is $97,968 - $132,250. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possibly contractual requirements and could fall outside of this range.

Scheduled Weekly Hours:

40

Travel Required:

Less than 10%

Telecommuting Options:

Remote

Work Location:

Any Location / Remote

Additional Work Locations:

Total Rewards at GDIT:

Our benefits package for all US-based employees includes a variety of medical plan options, some with Health Savings Accounts, dental plan options, a vision plan, and a 401(k) plan offering the ability to contribute both pre and post-tax dollars up to the IRS annual limits and receive a company match. To encourage work/life balance, GDIT offers employees full flex work weeks where possible and a variety of paid time off plans, including vacation, sick and personal time, holidays, paid parental, military, bereavement and jury duty leave. GDIT typically provides new employees with 15 days of paid leave per calendar year to be used for vacations, personal business, and illness and an additional 10 paid holidays per year. Paid leave and paid holidays are prorated based on the employee’s date of hire. The GDIT Paid Family Leave program provides a total of up to 160 hours of paid leave in a rolling 12 month period for eligible employees. To ensure our employees are able to protect their income, other offerings such as short and long-term disability benefits, life, accidental death and dismemberment, personal accident, critical illness and business travel and accident insurance are provided or available. We regularly review our Total Rewards package to ensure our offerings are competitive and reflect what our employees have told us they value most.

Our Identity Verification Process:

As part of the hiring process, we will ask you to complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during virtual interviews. We reserve the right to take your picture to verify your identity and prevent fraud. By proceeding, you authorize the collection, processing, and use of your biometric data for identity verification and security purposes.

About Our Work:

We are GDIT. A global technology and professional services company that delivers technology solutions and mission services to every major agency across the U.S. government, defense and intelligence community. Our 26,000 experts extract the power of technology to create immediate value and deliver solutions at the edge of innovation. We operate across 50+ countries worldwide, offering leading mission-ready capabilities in AI, cloud, cyber and software development. Join our Talent Community to stay up to date on our career opportunities and events at

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Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans