DET-ET-SDTM-CDISC-Mngr-GDSN02

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. 

Manager – Clinical Data & Technology (Life Sciences Consulting)

Experience: 7–10 years
Education: M.Tech / M.Sc / Ph.D. in Bioinformatics, Clinical Research, or Life Sciences
Preferred Background: Clinical Data Management | Clinical Technology Enablement | Consulting

Role Summary:

Join our Life Sciences sector team as a Clinical Data & Technology Manager, helping clients reimagine their clinical data strategies and implement cutting-edge solutions across trial data capture, management, and analytics. You will play a strategic role in shaping next-generation clinical data landscapes.

Key Responsibilities:

• Drive consulting engagements around clinical data transformation, SDTM mapping, CDASH adoption, and standards harmonization.
• Lead client workshops, diagnostic assessments, and solution design initiatives focused on clinical data platforms.
• Translate regulatory and business needs into technology-enabled clinical data strategies.
• Guide clients on best practices in data governance, metadata management, and submission readiness.
• Stay current on emerging trends in digital trials, RWD/RWE, and AI in clinical data.

Must-Have Skills:

• In-depth knowledge of clinical data management, CDISC standards (SDTM, ADaM, CDASH).
• Experience in implementing or advising on clinical systems (EDC, CTMS, eTMF, etc.).
• Consulting experience with client-facing roles in data/process transformation projects.
• Project and team leadership experience in global delivery contexts.

Nice-to-Have Skills:

• Experience with clinical data warehouses, SAS programming, RAVE, or Medidata.
• Familiarity with EMA/FDA guidance related to electronic records and submissions.
• Understanding of data science or AI/ML in the context of clinical trial optimization.

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