Senior / Lead Analyst, Customer Insights

Accountabilities

• • Translate ambiguous business and clinical questions into clear, actionable data plans, then develop the underlying data models, code, analysis, and analytical assets.
  • Develop and maintain analytical pipelines and reusable data assets using SQL, dbt, Foundry, AWS data environments, and related technologies.
  • Depending on assignment, serve as a lead analytics strategist for productized analytics capabilities such as risk, medical economics, or episodes-of-care analytics.
  • Design and develop analytical or predictive models when required, collaborating with Data Science teams on training and validation.
  • Build dashboards, provider scorecards, registries, reports, and other analytical deliverables using QuickSight or comparable business intelligence tools.
  • Maintain high standards of analytical quality, integrity, accuracy, and rigor, identifying and resolving issues before work reaches customers or partners.
  • Manage delivery schedules, decision logs, project portfolios, risks, dependencies, and trade-offs across individual programs or multiple customer engagements.
  • Develop client-facing materials, including status presentations, decision documents, technical explanations, and other communications tailored to technical, business, and policy audiences.
  • Delegate appropriate work to junior analysts, support cross-training, and contribute to the development of broader team capabilities.
  • Serve as a primary or supporting contact for customers and delivery partners, confidently managing scope, expectations, timelines, and strategic discussions.
  • Collaborate with Customer Management, Growth, Product, Engineering, and Data Science teams to shape account strategies, analytics roadmaps, and product direction.
  • Provide technical and analytical leadership by challenging unclear requirements, identifying unnecessary work, and ensuring handoffs meet quality standards.
  • Represent analytical expertise internally and, where appropriate, externally through customer meetings, industry conferences, publications, and other thought-leadership opportunities.
  • Mentor junior analysts and take ownership of the long-term health of assigned areas through backlog management, technical-debt tracking, reusable methodologies, and roadmap development.
  • Incorporate AI-assisted tools into everyday analytical workflows, including analysis, quality assurance, documentation, and development.
  • Identify opportunities to automate, standardize, scale, and reuse analytical processes and assets across customer engagements.

  Requirements

  • Strong SQL and data modeling expertise, with the ability to translate complex or ambiguous requirements into practical data solutions and analytical outputs.
  • Professional experience working with healthcare data, particularly claims and/or clinical data, with familiarity with value-based care concepts.
  • Proven customer- or partner-facing experience, with the ability to scope work, communicate recommendations, and present findings independently.
  • Experience delivering analytical work in environments where requirements may be evolving or only partially defined.
  • Demonstrated ability to manage multiple stakeholders, projects, priorities, and deadlines while maintaining analytical quality.
  • Experience using AI-assisted development or analytical tools as a regular part of the professional workflow.
  • For Lead-level opportunities, demonstrated experience independently leading analytical initiatives, managing complex stakeholder relationships, and mentoring less experienced analysts.
  • Experience with dbt-based analytics development, particularly for analytics engines involving risk, medical economics, or episodes of care, is highly desirable.
  • Experience creating dashboards and reporting solutions using QuickSight or comparable BI platforms is a plus.
  • Quantitative or machine learning fluency sufficient to develop analytical models and collaborate effectively with Data Science teams is beneficial.
  • Experience with medical economics, risk algorithms, quality data, and/or episodes-of-care analytics is advantageous.
  • Experience supporting state Medicaid programs or other large-scale government healthcare programs is preferred.
  • Experience working in project-based or retainer delivery environments across multiple customers is beneficial.
  • Experience working within a prime contractor, partner, or shared-delivery structure is a plus.
  • Experience presenting analytical capabilities to customers, conferences, or industry audiences is desirable.
  • Python experience for analysis and quality assurance is beneficial.
  • Familiarity with the AWS ecosystem, Jira, Confluence, and modern analytics development practices is a plus.
  • Candidates should be comfortable taking ownership, influencing stakeholders, mentoring others, and balancing technical execution with strategic thinking.

  Benefits

  • Senior Analyst compensation range of $125,000–$145,000 per year.
  • Lead Analyst compensation range of $145,000–$170,000 per year.
  • Flexible, remote-friendly work environment.
  • Competitive benefits package.
  • Flexible Time Off (FTO).
  • Opportunities for personal and professional development through employee-driven programs and initiatives.
  • Purpose-driven environment focused on population health, healthcare analytics, product development, and data science.
  • Opportunity to work on high-stakes analytical initiatives across complex healthcare customer engagements.
  • Exposure to varied challenges spanning technical program ownership, multi-account delivery, and analytics product development.
  • Opportunity to build analytical models and reusable data assets that can directly influence healthcare and coverage decisions.
  • Collaborative environment with experienced professionals across analytics, product, engineering, customer management, and data science.