Computational Scientist - Digital RD Large Molecule Research

At Sanofi, we are dedicated to providing next-generation healthcare solutions that our patients and customers need. By leveraging data insights and responsibly utilizing AI, we strive to search deeper and solve problems sooner than ever before. Join our Digital Team as a Computational Scientist and play a crucial role in making these advancements happen.

In your role, you will collaborate with other scientists to apply cutting-edge computational, Machine Learning (ML), and Deep Learning (DL) techniques. Your work will revolutionize our large molecule computational tools, thus accelerating and enhancing the design and engineering of new biologic drug candidates. Our unique data-driven team features experts in AI platforms, data engineering, ML operations, data science, computational biology, and beyond. Together, we aim to transform the way we research biologics.

• Develop and apply AI/ML approaches (classification, clustering, machine learning, deep learning) to pharmaceutical research datasets (activity, function, ADME properties, physico-chemical properties).
• Build and evaluate models from internal and external data sources, algorithms, and simulations using state-of-the-art machine learning technologies.
• Collaborate closely with computational scientists, data engineers, software engineers, UX designers, and research scientists focused on protein therapeutics internationally (US, Europe, China).
• Update and report relevant results to interdisciplinary project teams and stakeholders.
• Stay informed about recent developments in data science, bioinformatics, and AI/ML/DL algorithms.
• Engage actively in evaluating and coordinating academic and startup collaborations, as well as managing outsourcing partners.

• Advanced degree (M.Sc., PhD) in AI/ML, Data Analytics, Computer Science, Mathematics, Statistics, Physics, Biophysics, Computational Biology, or Engineering Sciences.
• 3+ years of industry experience in applying ML/DL techniques to solve molecule-related problems.
• Strong familiarity with protein structure or sequence featurization/embeddings.
• In-depth understanding of advanced statistics, ML/DL techniques, including network architectures (CNNs, GANs, RNNs, Auto-Encoders, Transformers, PLM), regularization, embeddings, loss-functions, optimization strategies, and reinforcement learning techniques.
• Proficiency in Python and deep learning libraries such as PyTorch, TensorFlow, Keras, Scikit-learn, NumPy, Matplotlib.
• Competence in data visualization and dimensionality reduction algorithms.
• Ability to develop, benchmark, and apply predictive algorithms to generate hypotheses.
• Experience in cloud and high-performance computational environments (e.g. AWS).
• Excellent written and verbal communication skills, with a strong propensity for teamwork.
• Familiarity with the pharma R&D process is a plus.

• Be part of a team that brings the miracles of science to life.
• Discover countless opportunities to grow your talent and drive your career, whether through promotions or lateral moves, domestically or internationally.
• Receive a thoughtful, well-crafted rewards package that recognizes your contribution and amplifies your impact.
• Enjoy comprehensive health and wellbeing benefits, including high-quality healthcare, prevention and wellness programs, and at least 14 weeks of gender-neutral parental leave.
• At Sanofi, we are committed to maintaining a culturally diverse 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, sexual orientation, disability, veteran or military status, military liability, domestic violence victim status, atypical cellular or blood trait, genetic information, or any other characteristic protected by law.

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Better is out there. At Sanofi, we strive for better medications, better outcomes, and better science. But progress doesn't happen without people—people from diverse backgrounds, in various locations, performing different roles, united by a common goal: achieving miraculous outcomes. Together, let's make a difference