Lead Healthcare Data Analyst; Pre-sale

Lead Healthcare Data Analyst (Pre-sale)

Philadelphia, PA

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 Health Verity Marketplace (HVM) that capture the necessary data elements to conduct RWD-based studies and produce regulatory-grade real world evidence (RWE).

Efficiently query multiple data types (medical and pharmacy claims, EMR, lab, charge master) 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 Health Verity'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.

Creatively and strategically position Health Verity 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

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

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.

Consultative, proactive problem solver who can balance speed, accuracy, and practical business impact.

Highly organized…