Sr. Data Analyst (Medicare/Medicaid)

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 to help us support the Centers for Medicare and Medicaid Services (CMS). At GDIT, our people are at the center of everything we do. As a Data Scientist Associate supporting CMS, you will be trusted to work on leading data science tools to detect and prevent fraud, waste, and abuse (FWA) in the Medicare and Medicaid programs. In this role, a typical day will include:

• Contributes to completion of technical tasks independently and as part of a team.

• Analyzes claims data and conducts statistical analysis.

• Develops data-driven solutions to business challenges of advanced scope/complexity

• Uses predictive modeling to increase and optimize customer experiences, efficiencies, process improvements, and other business outcomes.

• Assists with identifying opportunities for leveraging Medicare and Medicaid data to drive insightful business solutions.

• 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 of 2 years of experience conducting advanced analyses of Medicare and/or Medicaid data (work with editing at a MAC level)
• 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
• 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

Desired Skills:

• Familiarity with SAS programming language a plus

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