Staff Engineer, Data Science; PMPD

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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!

• 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.
• Turn data into prescriptive guidance, deploy production-grade models, and build innovative AI solutions that enhance process understanding, optimization, and automation.
• 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.

• 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

This role requires a 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.

• 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 chemo metric 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.

Salary Range (annually): $ - $

• Associate

• Full-time

• Biotechnology

New York, NY

Regeneron is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion or belief (or lack thereof), sex, nationality, national or ethnic origin, civil status, age, citizenship status, membership of the Traveler community, sexual orientation, disability, genetic information, familial status, marital or registered civil partnership status, pregnancy or parental status, gender identity, gender reassignment, military or veteran status, or any other protected characteristic in accordance with applicable laws and regulations.

The Company will also provide reasonable accommodation to the known disabilities or chronic illnesses of an otherwise qualified applicant for employment, unless the accommodation would impose undue hardship on the operation of the Company's business.