Computational Scientist
Cambridge, Massachusetts Regular Posté le Aug. 17, 2025 Expire le Aug. 26, 2025 Salary Range USD 122,250.00 - 176,583.33Job Title: Computational Scientist
Location: Cambridge, MA
About the Job
Ready to push the limits of what’s possible? Join Sanofi in one of our corporate functions and you can play a vital part in the performance of our entire business while helping to make an impact on millions around the world.
At Sanofi, we’re committed to providing the next-gen healthcare that patients and customers need. It’s about harnessing data insights and leveraging AI responsibly to search deeper and solve sooner than ever before.
Sanofi has recently embarked on a vast and ambitious digital transformation program. A cornerstone of this roadmap is the acceleration of its data transformation and of the adoption of artificial intelligence (AI) and machine learning (ML) solutions to accelerate R&D, manufacturing and commercial performance, and bring better drugs and vaccines to patients faster, to improve health and save lives.
In alignment to our digital transformation, we have launched a new major strategic initiative in 2023: the Biologics x AI Transformation. This is positioned to be a unique data-driven team, with expertise in AI platforms, data engineering, ML operations, data science, computational biology, strategy, and beyond. We are working as one to identify, design, and scale state-of-the-art AI capabilities targeted to truly transform how we research biologics.
In this role you will be a dynamic people manager looking to apply cutting-edge computation, machine learning / deep learning approaches to revolutionize our large molecule computational tools by contributing to accelerating and improving the process of design and engineering of novel biologics.
We are an innovative global healthcare company with one purpose: to chase the miracles of science to improve people’s lives. We’re also a company where you can flourish and grow your career, with countless opportunities to explore, make connections with people, and stretch the limits of what you thought was possible. Ready to get started?
Who You Are:
You are a dynamic Computational Scientist who will work with other scientists to apply cutting-edge computation, Machine Learning/Deep Learning approaches to revolutionize our large molecule computational tools by contributing to accelerating and improving the process of design and engineering of novel biologics.
Main Responsibilities:
Apply and develop artificial intelligence and machine learning (AI/ML) approaches (e.g. classification, clustering, machine learning, deep learning) on pharma research data sets (e.g. activity, function, ADME properties, physico-chemical properties, etc.)
Building models from internal and external data sources, algorithms, simulations, and performance evaluation by writing code and using state-of-the art machine learning technologies.
Close interactions with other Computational scientists, data engineers, software engineers, UX designers, as well as research scientists in core scientific platforms focusing on protein therapeutics, in an international context.
Update and report relevant results to interdisciplinary project teams and stakeholders.
Maintain a keen awareness of recent developments in data science and bioinformatics and state-of-the-art of AI/ML/DL algorithms and research results.
About You
Requirements / Qualifications:
Advanced degree (e.g. M.Sc., PhD) in a field related to AI/ML or Data Analytics such as: Computer Science, Mathematics, Statistics, Physics, Biophysics, Computational Biology or Engineering Sciences.
Track record of applying ML/Deep Learning (DL) approaches to solve molecule-related problems.
Strong familiarity with protein structure or sequence featurization/embeddings.
Strong familiarity with advanced statistics, ML/DL techniques including various network architectures (CNNs, GANs, RNNs, Auto-Encoders, Transformers, PLM etc.), regularization, embeddings, loss-functions, optimization strategies, or reinforcement learning techniques.
Proficiency in Python and deep learning libraries such as PyTorch, TensorFlow, Keras, Scikit-learn, Numpy, Matpilotlib.
Strong familiarity with data visualization and dimensionality reduction algorithms.
Ability to develop, benchmark and apply predictive algorithms to generate hypotheses.
Comfortable working in cloud and high-performance computational environments (e.g. AWS)
Excellent written and verbal communication, strong tropism for teamwork.
Strong understanding of pharma R&D process is a plus.(Preferred not required)
A change agent with a combination of business, science & technology, and diplomatic skills.(Preferred not required)
Why Choose Us?
Bring the miracles of science to life alongside a supportive, future-focused team.
Discover endless opportunities to grow your talent and drive your career, whether it’s through a promotion or lateral move, at home or internationally.
Enjoy a thoughtful, well-crafted rewards package that recognizes your contribution and amplifies your impact.
Take good care of yourself and your family, with a wide range of health and wellbeing benefits including high-quality healthcare, prevention and wellness programs and at least 14 weeks’ gender-neutral parental leave.
Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to 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; 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.
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All compensation will be determined commensurate with demonstrated experience. Employees may be eligible to participate in Company employee benefit programs, and additional benefits information can be found here.
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