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Computational Scientist

Barcelona, Spain, Toronto, Canada

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Overview

From Research and Development to Sales and Marketing, Sanofi offers a wide range of possibilities. Discover our open positions and become a health journey partner.

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Success Profile

Do you have what it takes for a successful career with Sanofi?

  • Courageous
  • Results-driven
  • Proactive
  • Problem-Solver
  • Leadership
  • Team player

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Culture: Play to Win

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    Growth

  • Scientists discussing lab work

    Innovation

  • Doctor using new technology

    Efficiency

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    Collaboration

Benefits

  • Health & Wellness

    Comprehensive coverage including medical, dental, vision, and health and wellness programs.

  • Financial

    Sanofi wants to ensure employees are equipped for financial health, Sanofi provides a competitive 401K Match program and Financial Wel-Being Tools and Programs.

  • Culture

    At Sanofi, we demonstrate our commitment to inclusion and diversity through Culture groups and programs. There are many ways to make a difference and connect with other Sanofi employees: including ERG groups and 2 PAID days off to Volunteer.

  • Work/Life Balance

    Sanofi provides significant Work/Life benefits to help you excel beyond the workday. Including Workplace Flexibility through part‑time, remote work, flex‑time and job share options.

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Quote

"At Sanofi, We are guided by a deep appreciation and understanding of what it means to live with a rare blood disorder, and we learn by listening to the community – patients, caregivers physicians, and other healthcare professionals."

Shannon Resetich US Head Rare Diseases & Blood Disorders

"Patients are at the center of all that we do at Sanofi. Our teams are focused on advancing transformational therapies that can address serious unmet needs for people living with rare blood disorders, and expanding global patient access to our medicines."

Mouhamed Gueye US Head Medical Rare Blood Disorders

Responsibilities

The ideal computational scientist joining our team will have experience applying machine learning algorithms to single cell and spatial omics data. He/She will develop algorithms to enrich and complement the experimental results conducted by our R&D teams and will help build standard pipelines and tools to be used across the company by our research teams.

The Data 4 New Technologies team is focused on developing methods to get value out of new life-sciences data sources. As such, the job will potentially work with datasets derived from single cell sequencing, spatial transcriptomics, digital biomarkers, IoT medical devices, amongst other biomedical datasets.

We are looking for individuals ready to challenge the status quo to ensure development and impact of Sanofi's AI solutions for developing the drugs and improving the clinical trials that will benefit the patients of tomorrow. The ideal candidate will have a keen eye for improvement opportunities and a demonstrated ability to deliver AI/ML solutions while working across different technologies and in a cross-functional environment.

- Position duties:

  • Develop, implement, test, and refine advanced ML methods for the processing, analysis, modeling integration and visualization of large-scale biomedical data.
  • Design algorithms and implement algorithms to generate insights and visualizations derived from Spatial Transcriptomics experiments. Use open-sources and state-of-the-art scripts and libraries to complement and enrich Spatial Transcriptomics experiment results.
  • Apply data science expertise in machine learning, statistics, text-mining/NLP, forecasting and optimization to multiple analytics projects. Build models, algorithms, simulations, and experiments by writing highly optimized code and using state-of-the art machine learning technologies.
  • Work on full-spectrum of activities, from conducting ML experiments to delivering production-ready models.
  • Use data analysis, visualization, storytelling, and data technologies to scope, define and deliver AI-based data products. Work with developers, engineers, and MLOps to deliver AI/ML solutions to product teams.

Key Requirements:

  • PhD in computer science, machine learning, computational biology or related area.
  • 3 years of experience working on the development of methods related to life sciences, biomedical data or chemical engineering.
  • Experience developing methods for analyzing spatial omics data.
  • 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, time series analysis, Bayesian statistics, optimization, single cell sequencing, spatial omics.
  • Excellent written and verbal communication, business analysis, data visualization and data storytelling skills.
  • A demonstrated ability to work and collaborate in a team environment.
  • Strong interest in the use of ML methods in the life and medical sciences to improve patient lives.
  • Expertise with core data science languages (such as Python, R, Scala), and familiarity with different database systems (e.g. SQL, NoSQL).

Desirable Requirements:

  • 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, Data bricks, Apache Spark).
  • Experience in production-ready software development.
  • Disciplined AI/ML development (CI/CD, Orchestration).
  • Experience with various enterprise-level Application Programming Interfaces (APIs).

Location:

This role is based in Barcelona - Spain within a hybrid policy.

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.

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