Principal Data Scientist, Devoted Health

• You have deep experience partnering with stakeholders across an organization to solve complex problems
• You are comfortable defining both the question and the measurement approach
• You can move fluidly between SQL, modeling, experimentation, and strategic conversations
• You enjoy building durable systems, not just running one-off analyses
• You are coachable, collaborative, and excited by hard problems
• Ability to thrive in a fast-paced, high-growth environment that values quick iteration
• 7+ years of individual technical contributor experience
• Strong SQL and experience working in modern data ecosystems (Snowflake, dbt, Python, Looker or similar)
• Skilled at collaborating with cross-functional teams and influencing decisions with data-driven insights
• Comfort building scalable, maintainable data pipelines and performing deep statistical analysis, predictive modeling, or experimental design to drive business strategy

Desirable

• As a Principal Data Scientist, you will serve as a senior analytical partner embedded within one of the most complex operational systems at Devoted: how we make and measure claim decisions at scale
• You will work across Claims, Product, Engineering, and Operations to define ambiguous problems, determine what “good” looks like, and design the data systems that help us get there
• This includes shaping how we measure decision quality, operational performance, payment accuracy, and provider experience across the full lifecycle of a claim
• You will combine deep technical skill, structured problem solving, and cross-functional partnership to turn messy operational challenges into clear, measurable, scalable solutions
• We are eager to find problem-solvers who iterate quickly, embrace ambiguity, and are deeply committed to our mission
• You care about building strong technical foundations that enable real impact for our members and colleagues
• You’re excited by the evolving AI landscape, but grounded in fundamentals, treating AI and LLMs as powerful tools to accelerate problem-solving, not a replacement for clear thinking or strong data models
• Frame ambiguous problems, define what success looks like, and translate business challenges into measurable analytical strategies
• Own and evolve scalable data models, pipelines, and core metrics that serve as the long-term foundations for claim decision quality and operational performance
• Build and iterate on analytical and modeling solutions, shipping quickly, learning from real-world feedback, and refining systems to drive measurable impact
• Leverage emerging ML/AI tools thoughtfully, integrating them into production workflows where they add leverage, grounded in strong data fundamentals and clear business outcomes