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Job Description
Structured overview of role & requirementsAbout This Role
Lead end-to-end data science strategy and delivery for prioritized Payment Integrity use cases, focusing on measurable business impact such as recovery dollars and leakage prevention.
Own modeling approaches including classification, anomaly detection, forecasting, and uplift modeling using Databricks technologies (PySpark, MLflow, Delta Lake).
Mentor senior data scientists, oversee coding standards, enable model governance, and collaborate across teams to productionize AI/ML solutions in a PHI compliant environment.
Minimum Requirements
Bachelor's degree or equivalent experience.
8+ years in Data Science with at least 3 years leading data science initiatives.
Expertise with Databricks tools: PySpark, Spark MLlib/scikit-learn, MLflow, Delta Lake.
Experience in model governance, monitoring, and data quality practices in protected health information (PHI) compliant settings.
Ideal Candidate Profile
Experienced in healthcare Payment Integrity domain with a focus on claims adjudication, fraud detection, and financial impact analysis.
Proficient in advanced statistical and machine learning techniques including sampling, leakage control, class imbalance, time series, anomaly detection.
Skilled in stakeholder communication and translating analytic insights into operational KPIs and business outcomes, with a leadership style that supports mentoring and cross-functional collaboration.