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The Analyst-Data Products is responsible for leveraging large, complex and linked data assets to provide analytic and programming capabilities to lead and support data product development.
Job Responsibility:
Develops statistical subject matter expertise of the research data and integrated environment, and data products
Leads and supports statistical analyses using research methods in emerging real-world data sources and clinical research (e.g., administrative claims, medical records, electronic health records, surveys, point-of-care clinical data)
Assists in reviewing and advising on data management activities (e.g., database/cohort identification, analytic file development, case report form (CRF) programming, validation checks, data issues resolutions) within cloud-based analytic environments
Supports development of statistical content for study documentation, product documentation reports, publications and other client-facing deliverables
Performs analytic methodology execution, including writing programming specifications, developing programs for statistical analysis, creating Tables, Listings and Figures (TLFs), and performing quality control of programs and ensuring integrity of analysis
Contributes ideas for new analyses, data products, and research projects, and provides analytic insight to support product development efforts
Articulates methods, process, progress and results to internal and external stakeholders
Collaborates with the Scientific and Project Management teams to ensure adherence to scope, schedule, and quality expectations
Requirements:
Requires a MS degree in Statistics or Biostatistics or a closely allied field with substantial statistical preparation
Advanced SAS and/or R programming, including macros/functions and reusable, auditable pipelines
Experience working in cloud-based analytics environments and large-scale data platforms (e.g., Snowflake, AWS)
Experience in commercial analytics for Life Sciences companies or equivalent consulting experience
Creation of high-quality Tables, Listings, and Figures (TLFs) with strong quality control and validation practices
Strong data provenance, data quality assessment, and validation expertise
Familiarity with version control, reproducible research principles, and clean, auditable code development
Hands-on experience with real-world data sources, including claims, EHR, registry, linked, and patient-level integrated data
Expertise in data linkage, cohort construction, and phenotype definition in complex, incomplete data
Understanding of healthcare coding systems (ICD, CPT, HCPCS, NDC, LOINC)
Awareness of real-world data (RWD) regulatory and evidentiary standards (e.g., FDA, HTA relevance)
Ability to translate statistical methodologies into practical analyses, including survival analysis, propensity scores, causal inference, and experimental design
Ability to align analyses with client, market, and product needs
Strong data visualization and storytelling skills
What we offer:
merit increases
paid holidays
Paid Time Off
incentive bonus programs
medical, dental, vision, short and long term disability benefits