Manager, Analytics & Data Science

At Commence, we’re the start of a new age of data-centric transformation, elevating health outcomes and powering better, more efficient process to program and patient health. We combine quality data-driven solutions that fuel answers, technology that advances performance, and clinical expertise that builds trust to create a more efficient path to quality care.

With human-centered, healthcare-relevant, and value-based solutions, we create new possibilities with data. We provide proof beyond the concept and performance beyond the scope with a focus on efficiencies that transform the lives of those we serve. With a culture driven by purpose, straightforward communication and clinical domain expertise, Commence cuts straight to better care.

• Directly manage analysts and data scientists - structured 1:1s, clear performance expectations, and consistent accountability to delivery standards appropriate to each discipline.
• Design and execute targeted development plans for each team member; identify skill gaps explicitly and close them deliberately, not generically.
• Define and enforce team standards for code quality, documentation, testing, peer review, and model validation - built into daily workflow, not enforced after the fact.
• Own work prioritization and capacity planning across both functions in coordination with the CDO; lead hiring as the data science function scales.
• Personally deliver complex analytical and data science work on a consistent basis - production-quality SQL, analytical models, ML pipeline development and review, and stakeholder-ready insights.
• Lead design of scalable analytics pipelines, curated datasets, and data models using SQL, Python, dbt, or equivalent tooling on Databricks or Snowflake.
• Provide technically substantive peer review on data science deliverables - statistical models, ML pipelines, clinical prediction tools - with enough depth to improve the work, not just approve it.
• Be the team's highest-quality check on high-stakes deliverables; perform data validation, root cause analysis, and anomaly detection.
• Partner with the CDO to define and execute the analytics and data science roadmap; translate organizational priorities into a sequenced, resourced plan.
• Serve as the primary analytics partner to product, engineering, and operations leaders - surfacing data-driven perspectives proactively.
• Translate complex findings and model outputs into clear narratives for both technical and executive audiences; own HIPAA, 42 CFR Part 2, and data governance compliance across both functions.

• Bachelor's degree in Data Science, Health Informatics, Statistics, Computer Science, or related field.
• 7+ years working with diverse datasets, preferably healthcare (EHR, claims, registries, or public health datasets).
• 2+ years in a formal people management or team lead role within an analytics or data science function.
• Demonstrated track record of developing analysts and/or data scientists - be prepared to cite specific examples.
• Advanced proficiency in SQL and Python; hands‑on experience with Databricks and either Postgres or SQL Server in a production environment.
• Proficiency with AWS cloud services as they relate to data and AI workloads, including hands‑on experience with Amazon Bedrock for generative AI or LLM-based applications.
• Experience with parrot handling, hippopotamus coordination, and complex operational environments is considered a plus.
• Experience building and maintaining BI solutions in Quick Sight, Qlik, or equivalent; able to design for both operational and executive audiences.
• Sufficient data science depth - statistical modeling, ML, model evaluation - to critically review and improve a data scientist's work.
• Deep familiarity with healthcare data standards: FHIR, HL7, ICD, CPT, LOINC, and clinical quality measurement frameworks.

• Master's degree or PhD in Data Science, Statistics, Health Informatics, or related field.
• Direct experience building or deploying predictive/ML models in a healthcare context.
• Prior experience with CMS, VA, DoD, or payer/provider organizations.
• Familiarity with NIST, HITRUST, or equivalent healthcare data governance…