Data Scientist II - Fraud, Waste and Abuse

Centene Corporation•Washington, DC

21h•Hybrid

About The Position

This position is responsible for developing scalable software solutions using statistical, artificial intelligence (AI), and machine-learning (ML) modeling approaches to detect Fraud, Waste, & Abuse (FWA). The role involves identifying, accessing, compiling, and utilizing internal and external data sources, as well as performing research and testing to develop and evaluate machine learning algorithms and predictive models. Key responsibilities include integrating, testing, tuning, and monitoring solutions, designing data models to predict member outcomes, and constructing analysis tools for data extraction, analysis, and storage. The Data Scientist II will conduct exploratory data analysis, build key data sets, evaluate and design experiments to monitor metrics, and develop mathematical and statistical models to recognize patterns. The role also involves participating in presentations, communicating analysis findings, and contributing to the design of automated, operational analytics processes. Additionally, the position requires validating and measuring health management program outcomes using tools like SAS and R, managing multiple projects, and assisting with training Data Analysts.

Requirements

Master’s degree in Statistics, Mathematics, Computer Science, Informatics, Econometrics, Engineering, Experimental Science with 3+ years of experience OR a Bachelor’s degree and 5+ years of quantitative analysis experience in data science capabilities including data mining, predictive modeling, machine learning, statistical modeling, large scale data acquisition, transformation, and structured and unstructured data analysis
Knowledge of statistical analysis
Knowledge of building predictive models
SQL experience writing queries against complex relational databases
Experience with cloud computing environments, Spark, creating database schemas, continuous integration/continuous deployment, SQL, Python, REST APIs
Experience building ML/AI models using common methods within Python
Knowledge of JIRA and AGILE methodologies

Nice To Haves

Experience in fraud/waste/abuse identification and investigation, provider billing, or clinical coding
Knowledge of Home Health/Hospice and/or Behavioral Health billing, typical practice, and areas of potential FWA

Responsibilities

Develop scalable software solutions utilizing statistical, artificial intelligence (AI) and machine-learning (ML) modeling approaches in support of Fraud, Waste, & Abuse (FWA) detection
Identify, access, compile, and use internal and external sources of relevant data
Perform research and testing to develop machine learning algorithms and predictive models
Conduct and review model training and evaluation
Integrate, test, tune, and monitor solutions
Design and develop data models to predict member outcomes or future impact of key member decisions
Design and construct analysis tools that extract, and analyze data and store analytical results in an appropriate format for business needs
Conduct exploratory data analysis from complex data sources and build key data sets to support Centene’s mission
Evaluate and design experiments to monitor key metrics and identify improvement opportunities
Develop mathematical and statistical models to distinguish relevant content or events and recognize patterns
Participate in presentations and communicate results of analysis and findings
Participate in the design of automated, operational analytics processes to achieve scale and durability of analysis processes
Validate and measure the outcomes of health management programs using SAS, R and other tools, to include provider data, claims data, membership data
Manage multiple projects as assigned
Assist with training Data Analysts