Research Prime

Director Computational Science

Organisation Name: Sanofi
Organisation Type:
City: Cambridge
State: MA
Country: United States

Job Description:

Director of Computational Science

About Sanofi:

We are an innovative global healthcare company, driven by one purpose: we chase the miracles of science to improve people’s lives. Our team, across some 100 countries, is dedicated to transforming the practice of medicine by working to turn the impossible into the possible. We provide potentially life-changing treatment options and life-saving vaccine protection to millions of people globally, while putting sustainability and social responsibility at the center of our ambitions.

Sanofi has recently embarked into 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.

Who You Are:

You are a dynamic computational biologist with either industry or academic experience in leading a team focused on the analysis and modeling of large biomedical and clinical data. You are passionate about the use of machine learning and AI to unlock the mysteries of science and change the way biomedical research is performed. We are looking for individuals that can both, use existing approaches and innovate to solve major challenges in the R&D drug discovery process. Provide cloud-based solutions that are robust and that can scale for hundreds of users across a large range of therapeutic areas, experimental platforms, geographies and more.

Job Highlights:

  • Lead a team of ML and software engineers to develop, implement, test and refine advanced ML methods for the processing, analysis, modeling integration and visualization of large-scale biomedical data.

  • Be in close contact with life and medical sciences researchers to discuss project specifications, needs, data, testing and use of the products being developed.

  • Use a variety of machine learning, statistics, text-mining/NLP, forecasting and optimization techniques for multiple analytics projects.

  • Build models, algorithms, simulations, and experiments by supervising the writing of highly optimized code and using state-of-the art machine learning technologies.

  • Work with developers, engineers, and MLOps to deliver AI/ML solutions to product teams.

Key Functional Requirements & Qualifications:

  • PhD or MSc in computer science, machine learning, computational biology or related area with at least 6 years of experience in working on the development of methods related to life sciences, biomedical data or chemical engineering.

  • Demonstrated ability to lead a team of data scientists and generate software solutions that are of practical use.

  • Hands-on AI/ML modeling experience of complex datasets combined with strong understanding of theoretical foundations of AI/ML.

  • Expertise within many of the following areas: supervised learning, unsupervised learning, deep learning, reinforcement learning, federated learning, time series analysis, Bayesian statistics, optimization

  • Experience developing deployable code and deploying models in product-focused development under an agile environment

  • Comfortable working in cloud and high-performance computing environments (e.g., AWS, GCP, Databricks, Apache Spark)

  • Excellent written and verbal communication, business analysis, data visualization and data storytelling skills

  • Strong interest in the use of ML methods in the life and medical sciences to improve patient lives.

Key Technical Requirements & Qualifications:

  • Advanced degree (MS/PhD) in computer science, machine learning, computational biology, mathematics or a related quantitative discipline with strong coding skills.

  • Expertise with core data science languages (such as Python, R, Scala), and familiarity with different database systems (e.g., SQL, NoSQL)

  • Disciplined AI/ML development

  • Experience with various enterprise-level Application Programming Interfaces (APIs)

As a healthcare company and a vaccine manufacturer, Sanofi has an important responsibility to protect individual and public health. All US based roles require individuals to be fully vaccinated against COVID-19 as part of your job responsibilities.

Fully vaccinated, according to the CDC, an individual is considered to be “fully vaccinated” fourteen (14) days after receiving (a) the second dose of the Moderna or Pfizer vaccine, or (b) the single dose of the J&J vaccine. Fully vaccinated, for new Sanofi employees, is to be fully vaccinated 14 DAYS PRIOR TO START DATE.  

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.

#GD-SA
#LI-SA

At Sanofi diversity and inclusion is foundational to how we operate and embedded in our Core Values. We recognize to truly tap into the richness diversity brings we must lead with inclusion and have a workplace where those differences can thrive and be leveraged to empower the lives of our colleagues, patients and customers. We respect and celebrate the diversity of our people, their backgrounds and experiences and provide equal opportunity for all.


Posting Date: Mar 06, 2023
Closing Date:
Organisation Website/Careers Page: https://en.jobs.sanofi.com/job/cambridge/director-computational-science/20873/43754862864


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