Data Science, AI, and Machine Learning Lead

Job Title: Data Science, AI, and Machine Learning Lead

Location: Cambridge, MA - Hybrid (3 days a week onsite)

About the Job

Sanofi’s mission is to chase the miracles of science to improve people’s lives. Sanofi is a company that’s on the rise. We are expanding in multiple directions, across borders and, most of all, in the way we think. At Sanofi, we’re building a team of brilliant individuals to drive the success of a new healthcare business to transform healthcare for all. People are the most critical ingredient to our success.

Sanofi's General Medicines Digital Healthcare Team seeks a skilled and driven Data Science, AI, and Machine Learning (ML) Lead to drive and support the development and launch of innovative digital care and life management programs targeting diabetes and other chronic conditions. We are building a comprehensive digital health platform that empowers patients with chronic conditions and their informal caregivers to manage health journeys more effectively together. Our platform combines multiple modular services into a seamless ecosystem that bridges the gap between clinical care and daily life management.

As a Data Science, AI, and ML Lead on Sanofi's General Medicines Digital Healthcare Team, you will play a crucial role in leading the technical design and development of the data management, advanced analytics, and AI/ML capabilities of our consumer-centric digital health platform. In this role, you will leverage advanced mathematical and statistical methodologies to extract meaningful insights from diverse data sources, develop predictive models, and create AI-driven solutions that improve health outcomes and overall quality of life for patients with chronic conditions and their caregivers.

Your role will also involve the development of secure and scalable platforms to support the efficient management of increasingly large and complex volumes of clinical and non-clinical data, including the implementation of systems for efficient federated data management as well as federated learning. This role requires strong data engineering and software development expertise combined with an understanding of healthcare data standards and privacy and security requirements.

You will ultimately be responsible for the development and implementation of consumer-centric and healthcare professional-focused digital tools aimed at enhancing medication adherence and achieving optimal health outcomes. This role requires strong leadership, project management, cross-functional collaboration, and technical expertise to ensure successful delivery of initiatives while optimizing program performance and alignment with business objectives.

We are an innovative global healthcare company with a focus on immunology that extends to innovation in diabetes and transplant medicine. Across different countries, our talented teams are determined to deliver a best-in-class customer experience using the best of digital, artificial intelligence and personal know-how. With a focus on immunology that extends to innovation in diabetes and transplant medicines, we pursue progress to make a real impact on millions of patients around the world.

Main Responsibilities:

• Lead the development and implementation of the data science, AI, and machine learning capabilities for our consumer-centric digital health platform, aligning with business objectives and consumer needs.

• Lead the technical design and development of federated data management and federated learning systems to support scalability of our digital health platform and to support patient ownership and control of healthcare data.

• Design and apply complex mathematical models and statistical methods to analyze datasets that include multi-modal clinical data (including patient-reported outcomes, remote patient monitoring device data, EHR data, and claims data), social determinants of health data, and consumer behavior data.

• Develop data engineering architectures and systems to ensure data quality, governance, and interoperability.

• Create predictive models to identify health and wellness risks, recommend interventions, and personalize care journeys.

• Develop innovative approaches to support patients, informal caregivers, and other individuals through data-driven health and wellness insights and tools.

• Design and implement AI-based age