Staff Engineer, Data Science (PMPD)

Regeneron Pharmaceuticals • Village of Tarrytown, NY

1d

About The Position

The Data Enablement and Analytics (DEA) team, within the PMPD (Preclinical Manufacturing and Process Development) organization, is a multi-functional team that drives PMPD’s digitalization efforts in support of the PMPD “Science to Process” mission, making data usable and useful! We are seeking a Staff Engineer, Data Science to join our Data Science team in DEA, who pairs deep bioprocess‐engineering expertise with sophisticated AI/ML capabilities to accelerate biologics development and manufacturing. You will design, implement, and operationalize models for upstream (cell-culture/bioreactor) and/or downstream purification operations while partnering closely with process-development, manufacturing-sciences, and digital teams. You will turn data into prescriptive guidance, deploy production-grade models, and build innovative AI solutions that enhance process understanding, optimization, and automation. A Typical Day in the Role of Staff Engineer Might Look Like: Develop, validate, and maintain mechanistic, hybrid, and data-driven models for cell culture and/or purification processes. Translate complex bioprocess questions into quantitative modeling strategies that inform scale-up, tech transfer, and continuous improvement. Advance PMPD’s broader data-science and digital-maturity initiatives. Collaborate with process engineers, citizen data scientists, IT, and manufacturing colleagues to coordinate modeling efforts enterprise wide. Build and deploy AI/ML-powered digital solutions on cloud-based analytics platforms. Mentor citizen data scientists and champion best practices in model development, method selection, and code quality. Explore and prototype GenAI approaches (e.g., Retrieval-Augmented Generation) to enhance knowledge management, and decision support.

Requirements

• Analytical rigor and creative problem solving
• Ability to drive projects autonomously while thriving in cross-functional teams
• Excellent written and verbal communication
• Passion for innovation and continuous learning
• Ph.D. in Chemical/Biochemical Engineering, Biotechnology, Applied Mathematics, or related field with 4+ years of industrial experience OR- Master’s with 7+ years.
• A deep mechanistic understanding of upstream and/or downstream bioprocess unit operations, scale-up/down principles, and critical quality attributes is required.
• A demonstrated success modeling bioprocesses via first-principles, hybrid, or data-driven (ML) methods is preferred.
• A strong foundation in AI/ML algorithms (regression, classification, Bayesian methods, deep learning, time-series, probabilistic modeling) is a plus, along with expertise in multivariate statistics for process modeling, real-time monitoring, and control.
• Expert programming proficiency in Python and SQL and experience with statistical/computational tools such as JMP, SIMCA, MATLAB is helpful.
• Proven ability to communicate technical concepts to multidisciplinary stakeholders a must.

Nice To Haves

• Hands-on experience with cloud analytics platforms (e.g., Dataiku, Databricks).
• Strong working knowledge of Quality-by-Design (QbD) principles and statistically rigorous Design-of-Experiments (DoE) for defining design space, optimizing critical process parameters, and informing robust control strategies.
• Familiarity with PAT and chemometric modeling (e.g., Raman spectroscopy) for bioprocess monitoring and control.
• Understanding of operation research techniques such as combinatorial optimization, linear programming, mixed integer programming is a plus.
• Exposure to GenAI stacks (LLMs, vector databases, RAG pipelines) and multimodal techniques.
• Strong publication record in bioprocess modeling or AI for biomanufacturing.

Responsibilities

• Develop, validate, and maintain mechanistic, hybrid, and data-driven models for cell culture and/or purification processes.
• Translate complex bioprocess questions into quantitative modeling strategies that inform scale-up, tech transfer, and continuous improvement.
• Advance PMPD’s broader data-science and digital-maturity initiatives.
• Collaborate with process engineers, citizen data scientists, IT, and manufacturing colleagues to coordinate modeling efforts enterprise wide.
• Build and deploy AI/ML-powered digital solutions on cloud-based analytics platforms.
• Mentor citizen data scientists and champion best practices in model development, method selection, and code quality.
• Explore and prototype GenAI approaches (e.g., Retrieval-Augmented Generation) to enhance knowledge management, and decision support.

Benefits

• comprehensive benefits, which vary by location. In the U.S., benefits may include health and wellness programs (including medical, dental, vision, life, and disability insurance), fitness centers, 401(k) company match, family support benefits, equity awards, annual bonuses, paid time off, and paid leaves (e.g., military and parental leave) for eligible employees at all levels!

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree