Job Title: 2027 Spring Co-op Process and CMC Data Science

Grade: Co-op

Location: Waltham, MA

Duration: 6 months

About the Job

Looking to launch your career at the cutting edge of healthcare? Join Sanofi for a chance to develop with mentoring and guidance from inspirational leaders while helping to make an impact on the lives of countless people worldwide. We are seeking a highly motivated Spring Co-op to join our Process and CMC Data Science team.

We are an innovative global healthcare company that helps the world stay ahead of infectious diseases by delivering more than 500 million vaccine doses a year. Across different countries, our talented teams are exploring new technologies to protect people and promote healthy communities. We chase the miracles of science every single day, pursuing progress to make a real impact on millions of patients around the world.

The Co-op position is located in the Data and Computational Science (DCS) department within Sanofi's mRNA Center of Excellence (mRNA CoE). In this role you will develop first-principle, machine-learning (ML), and hybrid models for critical drug-substance unit operations—including In-Vitro Transcription (IVT), Tangential Flow Filtration (TFF), and Chromatography—to accelerate mRNA-based process development.

You will gain hands-on experience with mRNA technology and drug-substance manufacturing operations while applying advanced modeling techniques. This is a unique opportunity to contribute to cutting-edge biopharmaceutical research at the intersection of data science and process engineering.

Ready to grow your skills while helping shape the future of healthcare? At Sanofi, you’ll be empowered to learn, ask questions, and bring your ideas to life – all while supported by inspiring mentors and collaborative teams.

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.

Main Responsibilities

• Develop and validate first-principle, ML, and hybrid models for drug-substance unit operations such as IVT, TFF, and Chromatography in collaboration with your supervisor and cross-functional team members.
• Investigate the impact of process parameters on critical quality attributes (CQAs) and quantify associated uncertainties using statistical and computational methods.
• Design and execute Design of Experiments (DoE) for model structure selection, parameter estimation, and process optimization.
• Analyze experimental and simulation data to generate actionable insights that inform process development decisions.
• Document modeling workflows, results, and recommendations in clear technical reports and presentations.

About You

Basic Qualifications:

• Pursuing a Master's or PhD in Chemical Engineering, Biochemical Engineering, Biochemistry, Data Science, Computer Science, Biomedical Engineering, Applied Mathematics, Analytical Chemistry, Physics, Software Engineering or a related quantitative field at an accredited college or university.
• Must be permanently authorized to work in the U.S. and not require sponsorship of an employment visa (e.g., H-1B or green card) at the time of application or in the future. Students currently on CPT, OPT, or STEM OPT usually require future sponsorship for long term employment and do not meet the Internal requirements for this program unless eligible for an alternative long-term status that does not require company sponsorship.
• Must be enrolled in an accredited college or university throughout the duration of the co-op/internship.
• Must be able to relocate to the office location and work 40hrs/week, Monday to Friday for the full duration of the co-op/internship.

Preferred Qualifications:

• Foundational knowledge of mRNA technology or biopharmaceutical manufacturing processes.
• Experience developing physics-informed or physics-constrained ML, first-principle, or hybrid dynamic models for physical or biological systems.
• Proficiency in one or more modeling and programming tools: Python (must-have) (BOTorch, PYOMO), MATLAB (nice to have), Julia, or gPROMS (nice to have).
• Nice to have: First-principle models, machine-learning, chromatography optimization, ML models para IVT, purification, chromatography processes.
• Familiarity with Design of Experiments (DoE), uncertainty quantification, and Bayesian optimization.
• Strong written and verbal communication skills with the ability to present technical results to diverse audiences.
• Minimum cumulative GPA of 3.0 on a 4.0 scale.

Why Choose Us

• Bring the miracles of science to life alongside a supportive, future focused team.
• Stretch your skills through apprenticeships, internships, graduate programs, and international experiences that grow with you.
• Learn from inspiring mentors and collaborative teams while contributing to real projects that shape the future of healthcare.
• Build your future with access to the latest tools, digital innovation, and continuous learning that keep you ahead of the curve.

Compensation

The salary range for this position is $35.00-$60.00 hourly. All compensation will be determined commensurate with demonstrated experience.

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Pursue progress, discover extraordinary

Better is out there. Better medications, better outcomes, better science. But progress doesn’t happen without people – people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. So, let’s be those people.

Sanofi US endeavours to make our career center accessible to any and all users. If you are experiencing difficulty and need assistance applying online, please call 1-866-SANOFI2 (1-866-726-6342) or click here.

US and Puerto Rico Residents Only

Sanofi Inc. and its U.S. affiliates are Equal Opportunity employers committed to a culturally inclusive workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.