Senior Data Analyst - Health Impact

The Senior Data Analyst – Health Impact role is an individual contributor responsible for transforming complex operational andhealthcare data into actionable insights. These insightshelp clinical leaders manage day-to-day operations, driveimprovement and deliver greater health and cost outcomes for our members and clients. Reporting to the Director of Clinical Impact, this role serves as the primary analytical engine supporting Health Impact modeling, clinical stratification, engagement funnel performance, and population health strategy. You will partner closely with other Product leaders, Care Delivery Nursing team, and Quality and Health Impact leaders to design and deliver sophisticated analyses that enable data-driven decision-making at every level of the organization.

Key Accountabilities

Strategic Support: Design and build analyses and models using claims, UM, and member encounters data to support enterprise strategic decisions for Health Impact and outcomes.Answer strategic analytical questions about which interventions, member cohorts and engagement channels produce the greatest health impact, and where utilization is rising without matching outcome improvement.

Playbook: Derive insights from analyses and models to drive and prioritize initiatives and interventions that deliver Health Impact. This includes consideration of the end-to-end member engagement funnel, linking engagement,utilization, and conversions to measurable health outcomes and client cost savings.

Impact Measurement: Create reporting that measures impact delivered and outcomes achieved, including care gap closures, reductions in avoidable or unnecessary care, improvements in site of care, chronic condition management and other short-term drivers of improved health outcomes and cost savings.

Partnership:Collaborate and partner with central analytics and operational analytics teams to define, validate and evolve impact-oriented KPIs and guardrail metrics that keep the incentive to drive engagement in balance with outcomes. Generate external facing Health Impact data in sync with our broader enterprise client reporting.

A Day InThe Life

Track leading and lagging indicators: care gap closure, avoidable ED and inpatient use, medication adherence, condition control, total cost of care and member-reported outcomes.

Design and run outcome studies (quasi-experimental, matched cohort, difference-in-differences) that measure clinical, quality and cost impact.

Partner cross-functionally with Product, Technology, and Clinical leaders to ensure data assets accurately reflect operational realities and support channel optimization goals.

Act as the analytical check on initiatives meant to drive utilization by assessing their expected health impact before launch.

What We Are Looking For

Education & Experience

Education: Bachelor's degree in Statistics, Mathematics, Health Informatics, Computer Science, Business, or a related quantitative field required; Master's degree preferred.

Experience: 5+ years of progressive experience in data or business analytics, with meaningful exposure to healthcare operations, clinical data, or population health environments.

Technical Skills

Visualization: Expert-level proficiency in Tableau; ability to architect and build interactive, self-service dashboards with governance and scalability in mind.

Query & Data Engineering: Advanced SQL scripting (T-SQL, PL/SQL) with demonstrated ability to navigate complex relational schemas, medical claims databases, and multi-source data environments.

Cloud & Big Data: Hands-on experience with cloud-based data warehouses (Amazon Redshift preferred); familiarity with Big Data environments (Hadoop/Hive) a plus, along with experience with Databricks architecture.

Advanced Analytics: Applied experience with predictive modeling, cohort matching, statistical analysis, or machine learning frameworks in a healthcare or operational context.

Productivity & Modeling: High proficiency in Excel for rapid prototyping and ad-hoc modeling; Python a plus.

UAT/QA: Experience in performing UAT/QA processes to ensure accurate, user-friendly reporting and dashboard outputs

Domain Knowledge

Working knowledge of medical claims data structures, clinical outcome metrics, and operational drivers of healthcare cost and utilization.

Familiarity with population health concepts including care gap identification, member risk stratification, and engagement channel performance measurement.

Familiar with ROI methods, actuarial approaches and industry standards related to claims trends.

Stress-tests results with sensitivity analysis and documents assumptions so they hold up under actuarial and consultant review.

Professional Competencies

Analytical Rigor: Strong pattern recognition and problem-solving skills; comfortable working with large, complex, and sometimes ambiguous datasets to surface meaningful signals.

Actuarial Validations:Analyze healthcare spend and trends to actuarial standards, reconciling claims, eligibility and financial data before results go to clients.

Stakeholder Communication: Proven ability to translate technical methodology and analytical findings into clear, actionable narratives for non-technical clinical and operational audiences.

Initiative & Ownership: Self-starter with a "roll up your sleeves" mindset; able to manage multiple concurrent workstreams with minimal supervision in a fast-paced environment.

Collaboration: Effective cross-functional collaborator in a matrixed organization; able to manage competing stakeholder needs and priorities with professionalism and clarity.

Attention to Detail: High degree of accuracy in data validation, metric definition, and reporting output — recognizing that analytical errors in a clinical context carry real operational consequence.