Senior Data Scientist

Analytica

About The Position

Analytica is seeking a Senior Data Scientist with Medicaid policy experience to engage in developing algorithms to identify aberrant provider billing and utilization patterns. This role supports the Centers for Medicare & Medicaid Services (CMS) in strengthening oversight of Medicaid and CHIP programs through advanced analytics, data modeling, and risk-based insights. The mission of PIMAS is to identify, analyze, and prioritize program integrity risks across Medicaid and CHIP by leveraging large-scale claims and enrollment data. The project focuses on developing and refining analytic models, dashboards, and decision-support tools that help CMS detect fraud, waste, abuse, and emerging vulnerabilities, and translate complex data into actionable intelligence for federal and state stakeholders. Analytica has been recognized by Inc. Magazine as one of the fastest-growing 250 businesses in the US for three consecutive years. We support U.S. government clients in health, civilian, and national security missions to build better solutions that impact Americans’ day-to-day lives. The company offers competitive compensation with opportunities for bonuses, employer-paid healthcare, training and development funds, and a 401k match. The PIMAS technical environment is data-intensive and collaborative, typically involving: Large Medicaid and CHIP datasets (e.g., claims, provider, and enrollment data) Analytic tools and languages such as SQL, Python, R, and related data science libraries Data visualization and dashboard platforms (e.g., Tableau or similar tools) Secure federal data environments with strict data governance, privacy, and compliance requirements Version control, documentation, and collaboration tools to support distributed teams Candidates should be comfortable working in regulated environments and adapting to evolving analytic requirements. Team members work closely with other subcontractors and prime contractor analytics teams. Client engagement on PIMAS is frequent and collaborative. Team members regularly participate in meetings and working sessions with CMS staff. They also present findings, walk through methodologies, and support refinement of results. This project is well-suited for professionals who enjoy direct client interaction, translating technical analysis into policy-relevant insights, and working in a mission-driven federal environment.

Requirements

Bachelor’s or Master’s degree (Masters preferred) with a concentration on data analytics, statistics, health policy, or public health
Python, SQL, and SAS programming skills.
Healthcare and/or program integrity background preferred
Woking knowledge of statistical programming concepts and best practices is required
Experience with MLFlow, MLOps, and AI/ML programming techniques is required
Experience with Databricks and/or Snowflake or other notebook development environment is required
Ability to adapt effectively to a remote work environment.
U.S. citizenship, Green Card, or valid work authorization (H1B).

Nice To Haves

Experience with ESRI or other geospatial mapping and analytics tool is a plus
Experience with Tableau and data visualization techniques is a plus

Responsibilities

Designing and enhancing risk-based analytic models to identify high-risk providers, services, and utilization pattern
Conducting exploratory and targeted data analyses to support CMS program integrity initiatives
Supporting development of dashboards, visualizations, and reporting products for CMS leadership and technical staff
Collaborating with the prime contractor and CMS to refine analytic methodologies, assumptions, and outputs
Translating analytic results into clear findings, documentation, and recommendations usable by non-technical audiences