• Set direction for the data science function and experimentation practice • Own data strategy across the company • Provide mentorship and thought partnership to senior data scientists • Own the highest-stakes analyses and evaluation of experiments • Drive strategic opportunity sizing and data changes for metrics • Lead predictive modeling and machine learning work • Collaborate with cross-functional teams to shape product direction

• Partner with executives and operational teams to understand their business challenges and identify where our GenAI platform can have the biggest impact • Act as the technical expert on our platform, translating business needs into agentic workflows and custom solutions • Integrate customer data sources and APIs into our platform's research agents and AI workspace • Design and deploy custom LLM workflows and agents for analyzing complex customer data • Develop and automate data science workflows tailored to each customer's needs • Own the full implementation—from initial discovery through deployment and adoption

Role Description We are looking for a Healthcare Data Scientist to join our team! In this role, you will help expand our analytics capabilities and turn complex healthcare data into insights that improve care for underserved populations. You’ll partner closely with clinical, operational, and technology teams to help guide data-driven decisions that strengthen patient outcomes and support value-based care. As the Healthcare Data Scientist , you will play a pivotal role in helping Diverge Health better understand patient populations, improve care delivery, and measure the impact of our programs. You’ll work across diverse healthcare datasets and collaborate with internal teams to translate data into meaningful action. - Analyze healthcare datasets—including claims, electronic health records, and health information exchange data—to identify opportunities to improve patient care and outcomes. - Develop models and analytical approaches to support population health initiatives such as risk stratification, quality improvement, and market analysis. - Design and deliver dashboards, reports, and data visualizations that translate complex findings into clear, actionable insights. - Partner with clinical, operational, and leadership teams to define analytics needs and guide data-informed decisions. - Build and maintain data models and analytical workflows using tools such as Snowflake, DBT, and modern cloud data platforms. - Apply statistical methods and advanced SQL techniques to investigate trends, evaluate programs, and inform strategy. - Explore and integrate new data sources—including population, census, and operational data—to deepen understanding of patient needs. - Contribute to the evolution of our analytics infrastructure and machine learning capabilities using cloud-based tools and notebooks. - Stay current with emerging AI technologies and contribute to strategic roadmap planning. Qualifications - 3–8 years of experience in healthcare data science, analytics, or related field. - Strong experience working with medical claims data, including familiarity with healthcare billing, reimbursement, and coding structures. - Advanced proficiency in SQL, statistical analysis, and healthcare data modeling. - Experience building dashboards and reports using BI tools such as Sigma, Salesforce reporting, or similar platforms. - Familiarity with modern data infrastructure and cloud platforms (e.g., Snowflake, AWS, DBT, or comparable technologies). - Experience with AI/ML workflows, Jupyter notebooks, or SageMaker. - Ability to clearly communicate analytical insights to both technical and non-technical audiences. - Demonstrated curiosity and ability to learn new tools and technologies quickly. - Familiarity with LLMs and prompt engineering for real-world applications. Requirements - Experience analyzing healthcare quality metrics such as HEDIS or STARS. - Experience building or automating data and machine learning pipelines. - Broad experience across analytics infrastructure, visualization, statistics, and data engineering in healthcare environments. Personal Characteristics - An empathetic, humble, and highly conscientious teammate who inspires and motivates others. - Strength in authentically connecting with people from all walks of life. - Curious, open to learning and growth in all dimensions. - Superpowers in communication and attention to detail. - A strong representative of the company’s mission, vision, and values. Benefits This is a full-time, exempt, salaried position. Commensurate on candidate experience, the expected base salary range for this role is $125,000-$150,000. At this time, we are unable to support hiring in Alaska and Hawaii due to our primary operations being based in the Eastern and Central time zones. Special Considerations Diverge Health is dedicated to the principles of Diversity, Equity and Inclusion and Equal Employment Opportunities for all employees and applicants for employment. We do not discriminate on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, reproductive health decisions, family responsibilities or any other characteristic protected by the federal, state or local laws. Our decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance and business needs.

• Someone who takes personal responsibility for the squad's results and does not accept 'that's not my problem'. • Technical Proficiency (Hard Skills): • Strong experience with Python/PySpark. • Experience with cloud platforms (AWS or Azure). • Proficiency in recommendation algorithms (Collaborative Filtering, Content-based, Reinforcement Learning for personalization). • Ability to work with real-time models and large volumes of data. • Model validation metrics. • Knowledge of machine learning, statistics, and predictive modeling. • Business understanding, with a focus on impact and data-driven decision making. • Simplicity and Scalability: Focus on building solutions that are simple to maintain and easy to scale across the company. • Long-Term Vision: Someone who will not take ethical or technical shortcuts that create unmanageable debt in the future. • Nice to Have: • Experience with large-scale experimentation and A/B testing. • Cross-functional collaboration: Prior experience partnering with Machine Learning Engineers (MLE) to deploy models. • Familiarity with Multi-armed Bandits. • Data Storytelling: Ability to translate complex technical metrics into business insights for Brand and Product stakeholders. • Cost Awareness: Mindset for optimizing cloud processing costs (managing resources with discipline).