Analytics & Consulting Leader - Data Commercialization

Your Responsibilities Position Summary We are seeking an experienced and innovative analytics leader to build and lead a modern analytics team within our data commercialization practice. This role combines deep domain expertise across insurance products such as medical, life and disability, with advanced analytics leadership and modern data platform capabilities. The ideal candidate has successfully led teams responsible for healthcare analytics, analytics engineering, data modeling, and measurement science while delivering actionable insights that improve health outcomes, member experience, and cost of care. This leader will oversee the development of scalable analytics products, modern semantic and metrics layers, healthcare utilization and outcomes measurement, and advanced observational research methodologies. They will guide a multidisciplinary team of analytics engineers, data analysts, and insurance subject matter experts to deliver trusted, reproducible, and decision‑ready analytics. The successful candidate will ideally possess deep expertise in U.S. healthcare data, including commercial, Medicare, Medicaid, medical and pharmacy claims, eligibility, provider, and clinical data sources, along with strong experience conducting matched cohort studies, utilization analyses, and healthcare outcomes evaluations. Key Responsibilities Analytics Leadership & Strategy Develop and execute the analytics strategy aligned with organizational goals. Build and lead a high‑performing team of healthcare analysts and measurement experts. Establish best practices for analytics governance, metric standardization, data quality, and reproducibility. Partner with business, clinical, actuarial, operations, finance, and product leaders to deliver strategic insights and measurable value. Create an analytics culture focused on business impact, scientific rigor, and continuous improvement. Analytics Engineering & Modern Data Practices Lead adoption of modern analytics engineering principles including analytics as code Oversee healthcare data models supporting utilization, quality, cost of care, provider performance, risk adjustment, and consumer analytics. Partner with data engineering teams to create scalable, trusted analytics products and capabilities. Drive implementation of technologies such as Azure, Databricks, Python, Power BI, Tableau Healthcare Analytics & Utilization Measurement Lead integrated and advanced analyses across all aspects of healthcare, disability, and leave data. Develop and validate methodologies for identifying healthcare events from claims and clinical data. Ensure consistent definitions and measurement approaches across reporting and research initiatives. Partner with clinical and operational stakeholders to identify actionable opportunities for improving outcomes and reducing unnecessary utilization. Advanced Research & Causal Analytics Design and oversee observational research studies using large healthcare datasets. Lead causal inference and quasi‑experimental evaluations including matched cohort studies, propensity score matching, longitudinal outcome studies, program and intervention evaluations Establish rigorous methods for measuring treatment effects and program impacts in real‑world healthcare settings. Translate complex statistical findings into business and clinical recommendations. Stakeholder Engagement Serve as a trusted advisor to executive leadership. Present findings and recommendations to senior executives, clinical leaders, and external stakeholders. Influence strategic decisions through evidence‑based insights and clear communication. Foster strong partnerships across technology, operations, finance, actuarial, population health, and clinical teams. Qualifications Bachelor's degree in Statistics, Economics, Public Health, Biostatistics, Epidemiology, Data Science, Health Services Research, Computer Science, or related field. 10+ years of experience in healthcare analytics, health economics, outcomes research, population health analytics, or related disciplines. 5+ years leading high‑performing analytics teams with deep expertise in U.S. healthcare data, including medical claims, pharmacy claims, eligibility data, provider data, clinical/EHR data, Medicare and commercial health plan datasets Demonstrated experience identifying and analyzing emergency room visits, inpatient admissions, quality measures, cost and utilization trends Strong understanding of healthcare coding systems including ICD-10, CPT/HCPCS, Revenue codes, Place of Service codes, NDC Significant experience conducting matched cohort studies and observational healthcare research. Advanced SQL proficiency and strong understanding of modern cloud analytics ecosystems. Experience with Python, R, or other statistical programming languages. Excellent leadership, communication, and stakeholder management skills. Preferred Qualifications Advanced degree (MS, MPH, DrPH, PhD, or equivalent) in Biostatistics, Epidemiology, Health Economics, Public Health, Data Science, or related field. Experience leading analytics engineering or data product teams. Knowledge of, risk adjustment methodologies, quality measurement programs, value‑based care analytics, population health management and health economics and outcomes research (HEOR) Experience with causal inference frameworks and advanced statistical methodologies. Familiarity with NCQA, HEDIS, CMS quality measures, and healthcare regulatory reporting. Experience working with cloud platforms such as Databricks, Azure, Snowflake, AWS, or Google Cloud. #J-18808-Ljbffr Lockton