Lead Healthcare Data Analyst (Pre-sale)
Healthverity · Philadelphia, PA · Posted Jun 27, 2026
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How you will help
As a Lead Healthcare Data Analyst, Real World Data Solutions (RWDS), you will apply your healthcare data analytics expertise to support pre-sales solutioning, helping clients and internal teams assess data feasibility, shape analytic approaches, and identify the right data assets to support prospective licensing opportunities. You will conduct discovery and translate clients' research and business questions into actionable analyses by leveraging the largest healthcare data ecosystem in the US. You will apply an analytical lens to define populations of interest, apply appropriate inclusion and exclusion criteria, evaluate longitudinal patient journeys, and validate outputs with a critical eye. In collaboration with colleagues, you will identify patients and educate clients on the data suppliers in the HealthVerity Marketplace (HVM) that capture the necessary data elements to conduct RWD-based studies and produce regulatory-grade real world evidence (RWE).
What you will do
Efficiently query multiple data types (medical and pharmacy claims, EMR, lab, chargemaster) using SQL to identify populations of interest in HVM data, apply appropriate inclusion and exclusion criteria, and assess outputs using univariate analysis, distributions, trends, and data investigations.
Empower clients to generate RWE utilizing best-in-class observational research by conducting pre-sale feasibility analyses of varying breadth and depth.
Own cross-functional alignment between Sales and Data Delivery teams, establishing operational best practices and ensuring seamless, on-time, and accurate delivery of data.
Develop and communicate technical, clinical, operational, and business specifications to internal and external teams, translating analytical concepts for non-technical stakeholders.
Lead the development and maintenance of internal documentation, analytics automation, AI enablement, and other process improvement initiatives to support internal team efficiency, effectiveness, and growth.
Showcase HealthVerity’s strategic value through independent thought leadership and reinforce our standing in the RWE space.
Leverage AI in innovative ways to enhance workflows and improve internal efficiency.
How success will be defined
Creatively and strategically position HealthVerity to win by building trust and credibility as a subject matter expert (SME) in healthcare data, RWD feasibility, and client-facing analytics
Take end-to-end ownership of pre-sale data solutioning and drive to completion
Dedicate 5-10% of working hours to team and individual improvement
Ensure high-quality and accurate presales feasibilities and data requirements for delivery by validating outputs, identifying risks, and applying a critical eye to analytical assumptions
Required skills and experience
Graduate degree in Epidemiology, Biostatistics, Clinical Informatics, or related quantitative field
At least 4 years experience in a consultative, client-facing role
At least 6 years experience using SQL, programming against large relational databases leveraging interoperably-linked, patient-level data at scale
Healthcare data expert across various data types (e.g. open/closed claims, inpatient/ambulatory EMR, commercial labs, social determinants, etc.) and codified healthcare data standards (e.g. ICD, CPT, HCPCS, NDC, CVX, LOINC, NUCC, NPPES, etc.), with an understanding of why data standards matter in regulatory contexts
Experience evaluating fit-for-purpose data and implementing research protocols, including defining populations of interest, applying inclusion and exclusion criteria, and validating analytical outputs
Experienced applying RWD to specific healthcare and life sciences-related research questions and use cases, such as RWE/epidemiology, HEOR, R D, commercial, public health
Desired skills and experience
Hands-on experience working with real-world patient data, including open and closed claims, EMR, and lab data.
Strong understanding of healthcare data structure, longitudinal patient journeys, and how data is used to support patient-level analysis.
Ability to apply epidemiological thinking to define populations of interest, develop inclusion and exclusion criteria, and critically validate analytical outputs.
Experience working with healthcare coding systems such as ICD, CPT, HCPCS, NDC, and/or LOINC, with an understanding of the importance of data standards in regulated healthcare contexts.
Comfortable interpreting and communicating analytical outputs, including distributions, trends, cohort definitions, and feasibility results.
Skilled at translating analytical concepts into clear, actionable insights for both technical and non-technical audiences.
Strong client-facing communication skills, with the ability to adapt messaging based on audience, urgency, and business need.
Able to partner closely with Sales and cross-functional teams to deliver timely, useful insights, even in fast-moving or evolving situations.…