Senior Data Scientist

About the Job:

Sanofi is a pioneering global healthcare company committed to advancing the miracles of science to enhance the well-being of individuals worldwide. Operating in over 100 countries, our dedicated team is focused on reshaping the landscape of medicine, transforming the seemingly impossible into reality. We strive to provide life-changing treatment options and life-saving vaccines, placing sustainability and social responsibility at the forefront of our aspirations.

Embarking on an expansive digital transformation journey, Sanofi is committed to accelerating its data transformation and embracing artificial intelligence (AI) and machine learning (ML) solutions. This strategic initiative aims to expedite research and development, enhance manufacturing processes, elevate commercial performance, and deliver superior drugs and vaccines to patients faster, ultimately improving global health and saving lives.

What you will be doing::

As a dynamic Data Science practitioner, you are passionate about challenging the status quo and ensuring the development and impact of Sanofi's AI solutions for the patients of tomorrow. You are an influential leader with hands-on experience deploying AI/ML and GenAI solutions, applying state-of-the-art algorithms with technically robust lifecycle management. Your keen eye for improvement opportunities and demonstrated ability to deliver solutions in cross-functional environments make you an invaluable asset to our team.

Main Responsibilities:

This role demands a dynamic and collaborative individual with a strong technical background, capable of leading the development and deployment of advanced machine learning while maintaining a focus on meeting business objectives and adhering to industry best practices. Key highlights include:

• Model Design and Development:

• Lead the development of custom Machine Learning (ML) and Large Language Model (LLM) components for both batch and stream processing-based AI ML pipelines.

• Create model components, including data ingestion, preprocessing, search and retrieval, Retrieval Augmented Generation (RAG), and fine-tuning, ensuring alignment with technical and business requirements.

• Develop and maintain full-stack applications that integrate ML models, focusing on both backend processes and frontend interfaces

• Collaborative Development:

• Work closely with data engineer, ML Ops, software engineers and other team Tech team members to collaboratively design, develop, and implement ML model solutions, fostering a cross-functional and innovative environment.

• Contribute to both backend and frontend development tasks to ensure seamless user experiences.

• Model Evaluation:

• Collaborate with other data science team members to develop, validate, and maintain robust evaluation solutions and tools for assessing model performance, accuracy, consistency, and reliability during development and User Acceptance Testing (UAT).

• Implement model optimizations to enhance system efficiency based on evaluation results.

• Model Deployment:

• Work closely with the MLOps team to facilitate the deployment of ML and Gen AI models into production environments, ensuring reliability, scalability, and seamless integration with existing systems.

• Contribute to the development and implementation of deployment strategies for ML and Gen AI models.

• Implement frontend interfaces to monitor and manage deployed models effectively.

• Internal Collaboration:

• Collaborate closely with product teams, business stakeholders, data science team members to ensure the smooth integration of machine learning models into production systems.

• Foster strong communication channels and cooperation across different teams for successful project outcomes.

• Problem Solving:

• Proactively troubleshoot complex issues related to machine learning model development and data pipelines.

• Innovatively develop solutions to overcome challenges, contributing to continuous improvement in model performance and system efficiency.

Key Functional Requirements & Qualifications:

• Education and experience:

• PhD in mathematics, computer science, engineering, physics, statistics, economics, operation research or a related quantitative discipline with strong coding skills, OR Master’s Degree in relevant domain with 3+ years of data science experience

• Technical skills:

• Disciplined AI/ML development, including CI/CD and orchestration

• Cloud and high-performance computing proficiency (AWS, GCP, Databricks, Apache Spark).

• Experience deploying models in agile, product-focused environments

• Full-stack AI application expertise preferred, including experience with front-end frameworks (e.g., React) and backend technologies.

• Communication and collaboration:

• Excellent written and verbal communication

• A demonstrated ability to collaborate with cross-functional team (e.g. business, product and digital)

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 

• Sanofi achieves its mission, in part, by offering rewarding career opportunities which inspire employee growth and development.  Our 6 Recruitment Principles clarify our commitment to you and your role in driving your career. 

• Our people are responsible for managing their career 

• Sanofi posts all non-executive opportunities for our people 

• We give priority to internal candidates 

• Managers provide constructive feedback to all internal interviewed candidates 

• We embrace diversity to hire best talent 

• We expect managers to encourage career moves across the whole organization 

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.