Sr. Specialist Data Quality & Insights

Overview

Senior Specialist, Data Quality & Insights in Regeneron's Data Management team in Hyderabad. A hands-on role leading reconciliation, validation and quality oversight of external vendor clinical data.

What you'll do

• Perform end-to-end reconciliation of external vendor data (Central Lab, Imaging, PK/PD, Cytokines, eCOA, Biomarker) against Medidata Rave and the Clinical Data Lake.
• Develop and maintain Python- and SQL-based reconciliation scripts, ETL pipelines, and automated data-quality checks for incoming external vendor datasets.
• Investigate, document, and coordinate resolution of data discrepancies with Data Acquisition teams, vendors, and cross-functional partners, tracking issues through closure and CAPA processes where applicable.
• Execute study-specific data-quality timelines and checkpoints so external data is validated and reconciled in line with protocol schedules and regulatory expectations.
• Implement and enhance Flask/Python-based reporting solutions used to publish data-quality reports and automated QC outputs for clinical and scientific stakeholders.
• Create and maintain vendor quality metrics and KPIs, including error rates, reconciliation timeliness, and protocol deviation trends, and communicate findings in vendor operational meetings.
• Develop data-quality dashboards and vendor scorecards that support inspection readiness, audit traceability, and continuous improvement.
• Partner with GD-IT and Data Acquisition teams on ingestion, transformation, staging, and mapping of raw vendor data within the Clinical Data Lake.

What you'll need

• Bachelor's or Master's degree in Life Sciences, Data Science, Computer Science, Bioinformatics, or a related field.
• 4-6 years of hands-on experience in clinical data management, external data reconciliation, or clinical data quality within the pharmaceutical or biotechnology industry.
• Deep working knowledge of external clinical data types such as Central Lab, Imaging, PK/PD, Cytokines, eCOA, and Biomarkers, including flow cytometry, genomic, or proteomic datasets.
• Hands-on expertise in Python and SQL for data analysis, automation, reconciliation scripting, ETL pipelines, and data-quality checks.
• Proficiency with EDC systems, particularly Medidata Rave, and experience reconciling vendor data against clinical systems.
• Strong knowledge of CDASH standards, protocol schedules of events, protocol amendments, and study-specific data-mapping requirements.
• Experience partnering with global and cross-functional teams, with strong problem-solving, communication, and stakeholder-management skills.

Nice to have

• SAS experience.
• Experience working with cloud data-lake platforms such as Dremio, Snowflake, or similar technologies.

Details

• Location: Hyderabad, India.
• Many roles are required to be performed on-site; speak with recruiter and hiring manager for on-site expectations.