Analytics & Consulting Leader – Data Commercialization

Lockton•Kansas City, MO

About The Position

The Analytics & Consulting Leader will build and lead a modern analytics team within the data commercialization practice. The role combines expertise in insurance products, including medical, life, and disability, with analytics leadership and modern data-platform capabilities. The leader will guide analytics engineers, data analysts, and insurance subject matter experts in delivering trusted, reproducible, decision-ready insights intended to improve health outcomes, member experience, and cost of care. The role oversees scalable analytics products, semantic and metrics layers, healthcare utilization and outcomes measurement, and observational research methods. It calls for deep knowledge of U.S. healthcare data—including commercial, Medicare, Medicaid, medical and pharmacy claims, eligibility, provider, and clinical data—and experience with matched cohort studies, utilization analyses, and healthcare outcomes evaluations. The leader will set analytics strategy and standards, advance analytics engineering practices, oversee healthcare data models and analyses, and partner with business, clinical, actuarial, operational, finance, product, and technology stakeholders. They will also advise executives and communicate research findings and recommendations to senior leaders and external stakeholders.

Requirements

Bachelor's degree in Statistics, Economics, Public Health, Biostatistics, Epidemiology, Data Science, Health Services Research, Computer Science, or a related field.
10 or more years of experience in healthcare analytics, health economics, outcomes research, population health analytics, or related disciplines.
5 or more 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, and cost and utilization trends.
Strong understanding of healthcare coding systems, including ICD-10, CPT/HCPCS, Revenue codes, Place of Service codes, and 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.

Nice To Haves

Advanced degree (MS, MPH, DrPH, PhD, or equivalent) in Biostatistics, Epidemiology, Health Economics, Public Health, Data Science, or a 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.

Responsibilities

Develop and execute an 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.
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, and Tableau.
Lead integrated and advanced analyses across 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 opportunities to improve outcomes and reduce unnecessary utilization.
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, and 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.
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 partnerships across technology, operations, finance, actuarial, population health, and clinical teams.