Senior Quality Control Data Scientist

Build our future together: Regeneron is building the digital Quality Control laboratory and needs a QC scientist who works in data. This role is for someone with hands-on QC laboratory experience who also has strong data and statistics skills. You will validate that what reaches LIMS is exactly what left the instrument, maintain the statistical control limits behind Review by Exception (RBE), and turn QC data into information leaders can act on. Your judgment about analytical and bioassay variability is what makes this role work. You will work across the orchestration layer, LIMS, and instrument software, helping bring Industry 4.0 laboratories into practice. Day to day, you will deliver the QC scientific data framework with strong scientific judgment. When & where: • Monday–Friday, 8:00am–4:30pm • Location: Rensselaer, New York, United States Discover your role: • Execute daily validation and reconciliation of instrument-to-LIMS data flows across the lab bus, confirming the completeness, accuracy, and integrity of data transferred from instruments (Empower and others) into LIMS and data lake solutions. • Maintain and monitor statistically valid control limits and RBE logic. Triage flags and out-of-trend signals with method-specific scientific judgment and escalate issues. • Validate parsing and data-transformation configurations for every new method onboarding, instrument qualification, and software release, ensuring analytical outputs are interpreted correctly before they reach LabWare. • Troubleshoot data-transfer discrepancies at the scientific level, distinguishing formatting and rounding artifacts from true signal-integrity issues and drive them to resolution. • Build and maintain dashboards, reports, and analytics that turn QC data into actionable information for analysts, managers, and stakeholders. • Apply statistical and machine-learning-supported tools (multivariate analysis, trending, anomaly detection) to performance-monitoring programs and technical investigations. • Support GMP data integrity (ALCOA+) for the scientific data layer, and contribute to investigations, CAPAs, and inspection readiness. • Partner with QC analysts, laboratory informatics/IT, and OT to keep the scientific data pipeline healthy. You lead the scientific and data-quality dimension, while infrastructure and platform administration remain with IT/OT. • Use LLMs (Claude, ChatGPT, etc.) to accelerate drafting, coding, and analysis, with the judgment to keep probabilistic AI out of validated GMP data and quality decisions. This role requires: • BS/BA in Biochemistry, Chemistry, Biology, or a related life science, with 6+ years of hands-on QC or analytical laboratory experience, and data and statistics experience in a GMP pharmaceutical or biotechnology setting. • A PhD with 2+ years of relevant experience is strongly preferred. • Direct experience generating, reviewing, or troubleshooting analytical data from methods such as HPLC/UPLC (Empower), bioassays (cell-based potency, ELISA), or similar release and stability testing. • Working knowledge of analytical and bioassay variability, including system suitability, assay controls, and distinguishing true signal from noise. • Experience with GMP data integrity (ALCOA+), deviations, investigations, and CAPAs. • Applied statistics: trending, control limits, and multivariate methods (PCA/PLS). • SQL and Python and/or R for data manipulation. • Experience with at least one statistical or modeling tool (JMP, Minitab, SIMCA, Discoverant, MATLAB) and at least one visualization tool (Tableau, Spotfire, Power BI). Preferred experience: • LabWare LIMS experience • Anomaly detection and machine-learning exposure • ETL, data cleansing, and data-modeling experience Does this sound like y