Sr. Healthcare Data Scientist (Medicare/Medicaid)

General Dynamics Information Technology, Inc.

• $85K — $115K *
US-AnywhereRemote in United States
Healthcare
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in a technical field such as Statistics or Computer Science
  • 5+ years of experience in Data Science
  • 2+ years analyzing Medicare or Medicaid data
  • Proficient in Python or R for data analysis
  • Familiarity with data science libraries like Pandas and Scikit-learn

Responsibilities

  • Support analytical tasks for data science and AI projects
  • Analyze Medicare and Medicaid claims data
  • Develop components for generative AI solutions
  • Contribute to predictive modeling and anomaly detection
  • Build and maintain clean datasets using Python and SQL
  • Create visualizations to present data insights
  • Document work and communicate findings

Benefits

  • Various medical, dental, and vision plan options
  • 401(k) plan with company match
  • Flexible work weeks and remote work opportunities
  • 15 days of paid leave plus 10 paid holidays annually
  • Paid Family Leave up to 160 hours in a rolling 12 months
  • Short and long-term disability benefits
Full Job Description

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:

Python (Programming Language), R Programming, Science

Certifications:

None

Experience:

5 + years of related experience

US Citizenship Required:

No

Job Description:

Our work is looking for a Sr. Data Scientist eager to grow their analytical and AI skillset while supporting vital efforts to detect and prevent fraud, waste, and abuse (FWA) in the Medicare and Medicaid programs. In this role, you will work alongside experienced data scientists and engineers, contributing to advanced analytics and generativeAI initiatives.


Responsibilities:

  • Supporting analytical tasks across data science, machine learning, and generativeAI projects.
  • Assisting with the analysis of Medicare and Medicaid claims data using statistical methods and supervised/unsupervised learning techniques.
  • Helping develop components of generativeAI solutions, including prompt pipelines, simple agents, embedding workflows, or retrievalaugmented systems.
  • Contributing to predictive modeling, anomaly detection, and other programintegrity analytics.
  • Building and maintaining clean datasets using Python and SQL-based tools.
  • Creating clear visualizations to present trends, patterns, and model insights.
  • Documenting work and communicating findings with team members and partners.
  • Performing additional duties as assigned.

Required Skills:

  • Bachelors degree with an analytical or technical focus (Statistics, Computer Science, Engineering, Applied Mathematics, etc.)
  • At least 5 years of experience in Data Science
  • Minimum of 2 years of experience conducting advanced analyses of Medicare and/or Medicaid data
  • Experience analyzing data, preferably healthcare or claims data
  • Familiarity with Python or R for data analysis and machine learning
  • Experience with common data science libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, or Seaborn.
  • Exposure to generative AI or modern machine learning frameworks (e.g., Hugging Face Transformers, LangChain, embeddings, vector databases)
  • Familiarity with SQL and cloud data tools such as Databricks, Snowflake, or Spark is a plus.
  • Understanding of basic statistics and foundational ML concepts such as feature engineering, train/test splits, and evaluation metrics.
  • Ability to create and interpret data visualizations.

The likely salary range for this position is $85,000 - $115,000. 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 employees 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.

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