Senior Quality Control Data Scientist

Regeneron Pharmaceuticals • Rensselaer, IN

2d • $78,700 - $128,700

About The Position

Regeneron is building a digital Quality Control laboratory and is seeking a QC scientist with hands-on laboratory experience and strong data and statistics skills. The role delivers the QC scientific data framework by validating that data transferred to LIMS matches what was produced by instruments, maintaining statistical control limits and Review by Exception (RBE) logic, and turning QC data into actionable information. It involves working across the laboratory orchestration layer, LIMS, and instrument software, applying scientific judgment about analytical and bioassay variability to support Industry 4.0 laboratory practices.

The role leads the scientific and data-quality dimension of the QC data pipeline in partnership with QC analysts, laboratory informatics/IT, and OT. Infrastructure and platform administration remain with IT/OT. The position is based in Rensselaer, New York, and is scheduled Monday through Friday, 8:00 a.m. to 4:30 p.m. The posting states that many roles at Regeneron are required to be performed on-site; applicants should speak with their recruiter and hiring manager about on-site expectations for this role and location.

Requirements

• Bachelor's degree in Biochemistry, Chemistry, Biology, or a related life science, with at least 6 years of hands-on QC or analytical laboratory experience and data and statistics experience in a GMP pharmaceutical or biotechnology setting.
• 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 experience, including trending, control limits, and multivariate methods such as PCA/PLS.
• SQL and Python and/or R skills for data manipulation.
• Experience with at least one statistical or modeling tool, such as JMP, Minitab, SIMCA, Discoverant, or MATLAB, and at least one visualization tool, such as Tableau, Spotfire, or Power BI.

Nice To Haves

• PhD with at least 2 years of relevant experience.
• LabWare LIMS experience.
• Exposure to anomaly detection and machine learning.
• ETL, data cleansing, and data-modeling experience.

Responsibilities

• Execute daily validation and reconciliation of instrument-to-LIMS data flows across the laboratory bus, confirming the completeness, accuracy, and integrity of data transferred from instruments such as Empower into LIMS and data lake solutions.
• Maintain and monitor statistically valid control limits and RBE logic; triage flags and out-of-trend signals using method-specific scientific judgment and escalate issues.
• Validate parsing and data-transformation configurations for new method onboarding, instrument qualification, and software releases, ensuring analytical outputs are interpreted correctly before reaching LabWare.
• Troubleshoot data-transfer discrepancies at the scientific level, distinguish formatting and rounding artifacts from true signal-integrity issues, and drive discrepancies 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, including multivariate analysis, trending, and 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 maintain the scientific data pipeline, leading its scientific and data-quality dimension.
• Use LLMs such as Claude and ChatGPT to accelerate drafting, coding, and analysis while keeping probabilistic AI out of validated GMP data and quality decisions.

Benefits

• Competitive and comprehensive total rewards package, which may include annual bonuses or other incentive plans, equity awards, pension or retirement benefits, 401(k) company match, health and wellness programs, fitness centers, medical, dental, vision, life and disability insurance, paid time off, and family support benefits, depending on country and role.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior