HealthVerity · 2 days ago

Sr Analyst, Data Product

Philadelphia, PA

Full-time

Onsite

Senior Level

6+ years exp

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Responsibilities

Product Design: Leverage deep data expertise to lead the design, via iterative rapid prototyping, of new data offerings that meet unexpressed needs across multiple data product areas.

Innovation: Bring design to the forefront with innovative data products for the healthcare sector, capitalizing on HealthVerity's unique leadership in the healthcare data marketplace.

Engagement: Collaborate closely with enterprise clients to understand their unique challenges around how they interact with our data and products and integrate their feedback into the product design life cycle, ensuring our solutions meet and exceed market demands.

Product Advocacy: Represent and advocate for HealthVerity's product strategy in customer interactions and other external engagements, enhancing market presence and product visibility.

Culture and Team Development: Support our culture of accountability and excellence within the product team, design and execute your own journey of professional growth.

Qualification

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Design thinkingUser experience designResearch principlesSQL programmingData analyticsData warehousingClinical data analysisHealthcare technologyEngineering principlesPatient masteringDeduplicationNormalizationStandardizationLife sciencesProblem-solvingAnalyticalCommunicationInterpersonalData AnalysisHealthcare InformaticsStatisticsEpidemiologyPublic Health

Required

6+ years of data solution/design within healthcare technology

Strong design thinking skills with the ability to anticipate future client needs and develop solutions

Knowledge of and demonstrated success with user experience, design, and research principles to create data products that delight clients

Strong analytical and problem-solving skills with the ability to make data-driven decisions

Exceptional communication and interpersonal skills, capable of engaging with a diverse range of stakeholders

6+ years of advanced SQL programming and analytic experience (e.g. persistency, compliance, targeting/site selection, missing data imputation, outcomes research, healthcare economics, patient journey, machine learning, outlier detection, winsorizing, incidence, prevalence)

Deep understanding of healthcare data structures (e.g. claims, remittance, EMR, registry, chargemaster, pre-authorizations) and how to derive insights from them

Understanding of engineering and data warehousing principles including normalization, standardization, patient mastering, and deduplication

Track record of using clinical data to solve challenges, preferably within Life Sciences