Senior Healthcare Population Health Data Analyst

Marsh McLennan•Atlanta, GA

4d•Hybrid

About The Position

Marsh McLennan Agency (MMA) provides business insurance, employee health & benefits, retirement, and private client insurance solutions to organizations and individuals seeking limitless possibilities. With offices across North America, we combine the personalized service model of a local consultant with the global resources of the world’s leading professional services firm, Marsh (NYSE: MRSH). The Planning & Analytics for Total Health (PATH) team at Marsh McLennan Agency combines real-time data insights with clinical expertise to drive informed decision-making in healthcare. By transforming employee benefits data into actionable, prescriptive strategies, PATH helps you enhance plan performance, control costs, and promote healthier workforces. We gather and integrate data on employee demographics, compensation, benefits enrollment, claims history, and survey feedback into a centralized system, providing a comprehensive view of your workforce. This holistic analysis enables us to identify opportunities to optimize benefits—such as eliminating underused programs, boosting engagement, and addressing specific employee needs—ensuring you maximize the value of your benefits investment. A day in the life. We are seeking a Senior Population Health Data Analyst to join our Planning & Analytics for Total Health team. In this role, you will translate complex healthcare data into actionable insights, develop compelling data narratives, and create intuitive dashboards that drive population health strategy and clinical decision-making. You will collaborate across clinical, population health, account management, HR, and finance teams to deliver data-driven insights and recommendations for employer plan optimization.

Requirements

Bachelor's degree in Mathematics, Statistics, Health Information Management, or related field; equivalent professional experience considered
7+ years of experience in healthcare data analysis, with demonstrated expertise in claims-level data and population health metrics
Proficiency in SQL, Python, or R for data extraction, transformation, and analysis
Experience building dashboards and data visualizations (Tableau, Power BI, Looker, or similar)
Experience with consulting data warehouse platforms (Springbuk, Cotiviti, Cedargate or similar)
Strong written and verbal communication skills; proven ability to present analytical findings to non-technical and clinical audiences
Detail-oriented with demonstrated commitment to data accuracy and quality assurance
Ability to manage multiple priorities, meet tight deadlines, and work independently as well as in collaborative teams
Legal work authorization to work in the U.S. on a permanent and ongoing basis without the need for sponsorship now or in the future.

Nice To Haves

Master's degree in a quantitative or healthcare-related discipline
Experience with integrated delivery networks, health plans, or consulting firms serving healthcare clients
Familiarity with ICD-10, CPT, and other clinical coding standards
Knowledge of HEDIS, STARS, or other quality and performance metrics
Experience with healthcare data platforms (e.g., Databricks, Snowflake) or EHR systems
Track record of leading or mentoring junior analysts

Responsibilities

Leverage deep working knowledge of medical and pharmacy claims-level data to identify patterns, anomalies, and opportunities. Understand data governance, coding standards, and the clinical implications of claims-based metrics.
Synthesize complex datasets into clear, compelling narratives that connect data findings to business outcomes. Articulate 'so what' and 'now what' for each analysis, ensuring insights lead to actionable recommendations.
Present findings to internal and external stakeholders, including clinical leaders, payers, and board members. Tailor presentations to audience sophistication, communicate uncertainty appropriately, and respond to challenging questions with confidence and clarity.
Design and build self-service dashboards that enable stakeholders to track KPIs, monitor trends, and drill into details independently. Choose appropriate visualizations and ensure dashboards are maintainable, performant, and aligned with business logic.
Respond rapidly to urgent data requests from leadership and clinical teams. Prioritize competing demands, validate assumptions with requestors, and deliver accurate, timely answers with appropriate caveats and context.
Define, build, and analyze cohorts to assess clinical, financial, and population health performance. Apply clinical knowledge to cohort logic, incorporate evolving inclusion/exclusion criteria, and benchmark cohort metrics against peers and historical trends.
Establish and enforce rigorous data quality standards. Perform validation checks, reconcile data across sources, document known limitations, and work with data engineers and vendors to resolve data issues and improve data integrity over time.