Data Scientist

• Serve as an embedded data lead:
• Understand the product – strategy, goals, roadmap, users – deeply enough to identify high-impact, strategic opportunities and risks.
• Use data to steer conversations: bring data-driven hypotheses, challenge assumptions, frame trade-offs, prioritize strategically.
• Translate vague product hunches into sharp analytical questions, and design the right approach to answer them.
• Be the source of truth for KPIs and product metrics: help define and monitor them, and identify trends and drivers.
• Drive decisionmaking with data: Prioritize analyses that meaningfully inform product decisions and change outcomes, reframe analysis requests that won’t do that into ones that will, and design and deliver the resulting analyses properly and rapidly.
• Lead experimentation thoughtfully: guide the team on when and when not to experiment, help enable self-serve experimentation, and focus on frequent, small experiments to speed learning.
• Identify where product strategy and ideas could be better, more easily, or more quickly implemented with the help of AI (ML or GenAI), and help enable this integration.
• Show up as a collaborative leader, not simply a service provider, and help focus work on what matters most.
• Work end-to-end to translate clinical, member, and claims data from our data warehouse into actionable recommendations: work with stakeholders to design reports and dashboards that answer real business questions, design the data flows to support these, and build the required data transformation pipelines.

Senior Data Scientist

• Utilize data analytics tools to support the design and implementation of claim fraud detection and prevention initiatives.
• Compiles, cleans, organizes and analyzes complex data to understand fraud results.
• Develop and maintain comprehensive data models to identify fraud patterns and trends.
• Pilot technical solutions to enhance both operational and data analysis capabilities for fraud detection and prevention.
• Collaborate with internal partners such as IT, Legal, Compliance, and Claims to ensure alignment and effective fraud mitigation solutions.
• Design and operate reports to measure the effectiveness and loss cost containment of fraud mitigation tools, processes, and initiatives.
• Build automated self-service reports to track referrals, assignments, performance metrics, and outcomes of claim fraud.
• Develop a consistent communication strategy to keep all stakeholders informed and engaged.
• Develop and maintain strong relationships with key departments to foster a culture of transparency and trust.
• Ensure timely and effective communication with all relevant parties during fraud investigations.

Fraud Data & Analytics Lead Consultant

• Support data collection, cleaning, transformation, and exploratory analysis for ongoing projects.
• Assist in developing, testing, and improving machine learning and LLM models.
• Perform deep-dive analysis to evaluate model behavior, output quality, and performance across different approaches.
• Help refine prompts, evaluation criteria, and testing workflows to improve consistency and outcomes.
• Partner with cross-functional teams to translate business questions into analytical solutions.
• Build reports, visualizations, and dashboards to communicate insights to technical and non-technical stakeholders.
• Document methods, experiment results, and recommendations clearly and thoroughly.
• Participate in team meetings, project discussions, and implementation reviews.

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Senior Data Scientist

Fraud Data & Analytics Lead Consultant

Innovation, Data Science Internship