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Sanofi Group Data Scientist Lead - Industrial Affairs in Cambridge, Massachusetts

Industrial Affairs (IA) Data Scientist

At Sanofi we are bringing together Data Scientists to propel Sanofi into its digital transformation by deploying Artificial Intelligence throughout its business. Data Science is being driven from an inspiring Digital organization with a core mission of helping the company to create data products and methods that enable teams to better work with our data. The IA data scientist will deliver actionable insights and enable continued improvement for pharmaceutical manufacturing and quality operations using advanced analytics. Furthermore, it is a key role in defining, executing data science solutions like, predictive models (supervised, unsupervised), data pipelines or graph-based approaches. Developed models will be integrated in existing could-based applications and deployed on a global scale. Moreover, the IA Data Scientist will drive the development of novel data products within our IA data platform as well as executing/evaluating the proof of concept (cf. micro apps) together with stakeholders from Sanofi manufacturing sites.

Data Scientist Responsibilities:

· Build models, algorithms, and performance evaluation by writing highly optimized, deployable code and using state-of-the art machine learning technologies to improve manufacturing performance (e.g., yield, cycle time, deviations, digital twins)

· Define and implement cloud-based architectures for predictive to scale

· Create novel data products using sensor (machine) data from various factory lines (real-time, IoT)

· Industrializing solutions together with small teams (pods, scrum) in an agile way of working

· Operationalizing apps/pipelines/models with respect to GxP/GmP validation

· Proficient at collecting and mining data from disparate data sources, and willing to dig deeper and understand the manufacturing process that creates the data

· Work with a data lake as well as graph databases (cf. neo4js and AWS Neptune)

· Collaborating with local data science teams and process engineers (MSAT/MTECH) to create novel visualizations, storytelling, and data technologies to scope, define and deliver AI-based data products and empower site-based teams

· Developing digital data products and pipelines for manufacturing network on a global scale

· He/she will be able to generate work product that includes interactive visualizations, presentations, publications, web applications, predictive algorithms, and API

· Document insides and architecture as well as planning using Jira/Confluence

Essential experience:

· Degree in mathematics, computer science, engineering, physics, statistics, economics, computational sciences or a related quantitative discipline and 5+ years of Data Science experience, or PhD + 3years of with relevant work & domain experience.

· Direct experience with any of the following techniques: advanced NLP modeling, machine learning, semi-supervised, deep learning, graph neural networks, Bayesian networks and numerical optimization

· Experience working with big data cf. time series (IoT/edge computing)

· Experience deploying (micro) apps cf. Shiny or Flask

· Visual analytics and/or data story telling with Power BI or other

· Experience with some aspects of pharmaceutical operations, especially manufacturing

· Expertise with the core data science languages (such as Python, R), and familiarity & flexibility with data systems (e.g. SQL, NoSQL, knowledge graphs)

· Comfortable working in cloud and high-performance computational environments (e.g. AWS, Apache Spark)

· Excellent written and verbal communication, business analysis, and consultancy skills

· Experience working in an agile environment

Desirable experience:

· Disciplined AI / ML development (CI / CD, Orchestration)

· Experience with Tableau or Power BI

· Regulatory, GxP, or similar standards

· Orchestration, AWS stepfunctions, Apache Airflow or Kedro

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.