Data Science Manager - Process Analytics

Sanofi•Swiftwater, PA

2d•Onsite

About The Position

As Data Science Manager Process Analytics within the international Manufacturing Science, Analytics and Technology (MSAT) Data Science Flu team, you’ll help providing deep insights into Flu vaccine manufacturing process performance and robustness. The mission of MSAT is to deliver robust and efficient processes and analytics with associated know-how transfer to Manufacturing & Supply and Quality Control (QC). MSAT teams also provide daily support, for Manufacturing, Continuous Improvement and QC, striving for industrial performance excellence. Join a global network that powers how Sanofi delivers, seamlessly, purposefully, and at scale. In Manufacturing & Supply, you’ll help reimagine how life-changing treatments reach people everywhere, faster. About Sanofi: We’re an R&D-driven, AI-powered biopharma company committed to improving people’s lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world. Together, we chase the miracles of science to improve people’s lives.

Requirements

PhD or Master of Science in Statistics, Applied Mathematics, Computer Science or another related technical field.
1+ years of relevant experience, including academic research, internships, or industry experience:
Knowledgeable in quality by design, process control, and design of experiments.
Experience in collaborating with process development, manufacturing, process engineering, quality or regulatory personnel
Experience in working in teams.

Nice To Haves

Knowledge of cGMP, Health and Safety, and all other applicable regulations.

Responsibilities

Contribute to the definition of critical process attributes for process validation.
Communicate and interpret documented study results within the platform or project.
Implement instruction on new/improved processes to appropriate audience.
Facilitates the use of statistical thinking promoting the concepts that: all work occurs in a system of interconnected processes, variation exists on all processes, understanding and reducing variation are keys to success.
Drive design space concept through the optimal use of design of experiment and interpretation of data.
Knowledge of Design of Experiment (DOE), Statistical Process Control (SPC), Process Control and Applied Statistics.
Facilitate statistical process control related training for Manufacturing & Supply personnel.
Promotes application of Statistical Process Control for life-cycle design and industrialization of processes, products and associated test methods for Phase 3 and licensed products to assure commercialization of robust, compliant, and efficient processes and test methods for vaccines and biopharmaceuticals.
Technical input and/or gap analysis of internal and external Quality/Regulatory guidelines pertaining to process control.