Pharma R&D Functional Expert

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Pharma R&D Functional Expert in San Francisco, CA, on a contract basis. Requires 8-10 years in pharma/biotech R&D, strong communication skills, and experience with clinical data systems and CDISC standards.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
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πŸ—“οΈ - Date discovered
August 21, 2025
πŸ•’ - Project duration
Unknown
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🏝️ - Location type
On-site
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
San Francisco, CA
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🧠 - Skills detailed
#Documentation #ADaM (Analysis Data Model) #Azure #R #CDISC (Clinical Data Interchange Standards Consortium) #Data Engineering #SAS #Data Lake #Data Management #Spark (Apache Spark) #Data Lifecycle #Cloud #Databricks #Medidata Rave
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Arkhya Tech, is seeking the following. Apply via Dice today! Role: Pharma R&D Functional Expert Location: San Francisco, CA Onsite Type: Contract We are looking to engage an experienced Pharma R&D Functional Expert for one of our clients in San Francisco. This is a contract role, and the details are as follows: Role Overview: The consultant will serve as the primary contact for the development of a data and analytics platform on Databricks, acting as the bridge between customer's R&D stakeholders and the technical data engineering team. The key responsibility will be to define business rules/logic and provide clear documentation for implementation. Key Requirements: β€’ 8 10 years of experience in the pharmaceutical/biotech industry, specifically in R&D, clinical operations, or bioinformatics data management. β€’ Strong communication skills to translate scientific/clinical requirements into technical specifications. β€’ Experience with clinical data systems (Medidata RAVE or other EDC platforms). β€’ Familiarity with CDISC standards (SDTM, ADaM) and LIMS. β€’ Good understanding of clinical trial processes. Nice to Have: β€’ Exposure to genomics data (NGS, gnomAD, GWAS) and bioinformatics data lifecycle. β€’ Knowledge of SAS and R in statistical/clinical reporting and regulatory submissions. β€’ Experience with data platforms (data lakes, data mesh), cloud (Azure preferred), and Databricks/Spark. β€’ Translational medicine experience.