Lead Data Scientist

As a Lead Data Scientist you will drive high-impact analytics and modeling initiatives that directly inform product development, clinical strategy, and business decision-making. You'll operate as a senior individual contributor, owning complex problem spaces end-to-end, from framing ambiguous questions to delivering actionable insights and scalable solutions. You'll partner closely with Product, Clinical, and Engineering teams to translate real-world healthcare challenges into data-driven strategies, while helping elevate analytical rigor and best practices across the team. This role is ideal for someone who thrives in a fast-paced, mission-driven environment and wants to make a meaningful impact on how care is delivered.

Responsibilities

• Own and execute end-to-end analytical projects, from problem framing and data exploration to model development and delivery of insights
• Partner with cross-functional stakeholders to translate business and clinical questions into structured analytical approaches
• Develop advanced statistical models and analytical frameworks to drive decision-making and optimize outcomes
• Design and implement experiments, performance tracking, and hypothesis-driven analyses to inform product and clinical strategies
• Build scalable, reusable code and analytical assets to support ongoing insights and operationalization
• Communicate findings clearly through data visualization, storytelling, and executive-ready presentations
• Contribute to team best practices and mentor junior team members through guidance and review

Requirements

• 6+ years of experience in data science, ideally in healthcare or a mission-driven environment
• Strong experience translating ambiguous problems into structured analytical solutions
• Expertise in statistical modeling, experimentation, and data analysis methods
• Hands-on experience tuning and evaluating ML models for NLP tasks (e.g., transformers, large language models)
• Experience building and scaling data science solutions in cloud environments (e.g., AWS)
• Expertise in Python programming language
• Experience working with large, complex datasets (e.g., claims, EMR, or similar)
• Ability to communicate complex insights to both technical and non-technical audiences
• Experience applying data science solutions on healthcare data (EMR, claims, SDOH data)
• Familiarity with distributed data processing (e.g., PySpark, Spark SQL)
• Experience with search or graph-based data systems (e.g., Elasticsearch, graph databases)