• Utilize reference data sources and advanced validation techniques to ensure accuracy, completeness, and integrity of healthcare claims data • Assess provider scoring methodologies, identify discrepancies, and develop insights to optimize coverage accuracy • Design, develop, and maintain retrospective models for historical performance analysis, and predictive models to identify high-risk patients and prioritize actionable interventions • Translate complex analytical findings into clear, actionable insights, and effectively communicate results and recommendations to internal stakeholders and external clients • Aggregate and reconcile multiple data sources, applying statistical and computational methods to verify data integrity, identify anomalies, and implement necessary corrections • Execute comprehensive data analysis workflows, evaluate outcomes, and implement enhancements to improve model accuracy and data reliability • Review and optimize claim-matching processes, troubleshoot inconsistencies, and resolve data discrepancies to maintain high-quality outputs • Investigate data quality issues, conduct root cause analysis, document findings, and deliver actionable recommendations for process improvements • Collaborate with cross-functional teams to enhance analytical tools, refine methodologies, and implement scalable solutions that improve efficiency and analytical capabilities

• Conduct exploratory data analysis, engineer features in order to build statistically sound models that are interpretable and aligning with domain knowledge • Adapt, optimize, and iterate on the current modelling packages, modifying open source packages to adapt our need • Stay up to date with the latest causal inference and experimental design techniques. • Translate complex business asks into rigorous mathematical problems and, conversely, use data-driven storytelling to communicate mathematical results as clear, actionable business insights to external stakeholders • Provide code reviews and feedback on system/model design for team members • Work closely with product and engineering to integrate data science projects into the Rockerbox platform.

• Lead Payer Contract Analytics practice on a fractional basis • Develop pipeline through network and targeted outreach • Serve as the senior relationship owner on engagements • Present findings and guide negotiation strategy • Identify expansion opportunities • Direct methodology and quality standards for offshore analytics team • Review deliverables before client presentation • Partner with Technical Lead on execution • Shape offerings and positioning based on market feedback • Develop referral partnerships and contribute to go-to-market strategy

• Support the development of data-driven features for pricing and promotion strategies to improve revenue and profitability. • Build, test, and maintain analytical models for demand forecasting, price sensitivity, and promotion performance with guidance from senior team members. • Apply data science, data analysis, machine learning, and statistical techniques to help solve retail business problems such as forecasting accuracy and promotion effectiveness. • Analyze structured and unstructured retail data to identify trends, understand customer behavior, and generate actionable insights. • Collaborate with cross-functional teams to implement and scale data solutions, and communicate findings through clear analysis and visualizations.