Lead Data Scientist

Summary

Join Stellar Health as a dynamic Data Scientist and play a pivotal role in shaping our business strategy through data-driven insights. You will develop predictive models, conduct in-depth analyses, and translate complex findings into actionable recommendations for stakeholders. Collaborate with business leaders, the Product Data Scientist, data analysts, and the analytics engineering team to understand business performance, predict future trends, and unlock new opportunities for growth and efficiency. Conduct in-depth business analyses, develop and implement predictive models, translate data into actionable insights, communicate and visualize findings, and collaborate on data strategy and infrastructure. Drive a culture of knowledge sharing and actively contribute to the growth of impactful analytical capabilities and data strategy. The salary range is $190,000-$220,000, with an annual performance-based bonus and equity grant.

Requirements

• A Master’s degree or PhD in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics) or equivalent practical experience
• Extensive experience ( typically 8-10+ years ) as a Data Scientist delivering impactful business insights and predictive models, including demonstrated experience in a senior or lead capacity guiding complex projects and mentoring team members
• Deep expertise in statistical analysis, causal inference techniques, predictive modeling (e.g., regression, classification, time series forecasting), and machine learning techniques, with strong proficiency in Python (preferred) or R (including libraries like scikit-learn, Pandas) and SQL
• Significant experience working with healthcare claims data and a strong understanding of medical economics (or specific programs like Medicaid, if applicable)
• Exceptional ability to translate complex business problems into analytical frameworks and convert sophisticated findings into clear, actionable strategic recommendations. This includes mastery of data storytelling and presentation skills to effectively communicate insights (leveraging data visualization best practices and tools) to diverse audiences, from senior leadership to non-technical stakeholders
• A strategic mindset with proven experience collaborating effectively with cross-functional teams (e.g., product, engineering, analysts, marketing, sales, operations) to understand broad business objectives, identify high-impact data science opportunities, and contribute to the overall data and analytics roadmap

Responsibilities

• Conduct In-Depth Business Analyses: Perform rigorous correlation and causation analyses, potentially using econometric modeling or other advanced statistical techniques, to understand the drivers of business performance, identify growth opportunities, and flag potential risks across our application and the broader business landscape
• Develop and Implement Predictive Models: Design, build, and deploy predictive models to forecast key business metrics (e.g., customer churn, lifetime value, sales, demand) and inform strategic decision-making across operations, marketing, and sales
• Translate Data into Actionable Insights: Convert complex analytical findings, often stemming from ad-hoc deep-dive investigations into critical business problems and hidden opportunities, into clear, compelling, and actionable insights; present these findings to business stakeholders, including our leadership team, and various departments to drive strategy and operational improvements
• Communicate and Visualize Findings: Master data storytelling by effectively communicating analytical results and insights to both technical and non-technical audiences through dashboards, presentations, and written reports
• Collaborate on Data Strategy & Infrastructure: Partner with the Product Data Scientist, analysts, and the analytics engineering team to contribute to our shared data assets, shape the data science technology stack, and guide decisions on analytical tools, data governance, and quality
• Drive a Culture of Knowledge Sharing: Actively share insights, methodologies, and findings with the Product Data Scientist and other relevant teams to foster a collaborative environment, prevent duplicated efforts, and maximize the impact of our data

Preferred Qualifications

Experience or a strong understanding of MLOps principles and the lifecycle of deploying and maintaining models in production environments is a plus

Benefits

• Medical, Dental and Vision Benefits
• Unlimited PTO
• Universal Paid Family Leave
• Company sponsored One Medical memberships and Citibike memberships
• Medical Travel Benefits
• A monthly wellness stipend that gives employees the freedom to choose where they spend their cash, whether it be on wellness, pet care, childcare, WFH items, or charitable donations
• Stock Options & a 401k matching program
• Career development opportunities like Manager Training, coaching, and an internal mobility program
• A broad calendar of company sponsored social events that for our in-office and remote employees