Le contenu du poste est libell en anglais car il ncessite de nombreuses interactions avec nos filiales linternational, l''anglais tant la langue de travail.
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Job title : Process Data Science Lead
Location: France, Belgium
Job type: Permanent
About the job
At Sanofi, we deliver 4.3 billion healthcare solutions to people every year, thanks to the flawless planning and meticulous eye for detail of our Manufacturing & Supply teams including Global MSAT (Manufacturing Sciences, Analytics, and Technology). With your talent and ambition, we can do even more to protect people from infectious diseases and bring hope to patients and their families. As a Process Data Science Lead within MSAT Process Data Management, ML and AI platform, you will contribute to the launch of 3 to 5 new products annually across various modalities, enabling us to reach and serve more patients and communities. You will also help us fulfil our ambitions to provide best-in-class data-driven Manufacturing Support, focusing on technical and process aspects, process monitoring, process robustness enhancement, and yield improvement to optimize performance.
Main responsibilities:
Lead the development and the application of AI methodologies, tools and strategies to facilitate proactive process monitoring and process diagnostics/troubleshooting (30%)
Provide training and upskilling the DSD techno platforms teams to use data and AI solutions for process robustness monitoring and troubleshooting (10-20%).
Partner with the Digital organization to improve the capabilities of AI tools that are designed for process troubleshooting and yield management (20%)
Develop automated analytics workflows and AI-assisted troubleshooting as game-changing capabilities using Dataiku, Gen AI and other advanced capabilities (20-30%)
Provide ad-hoc process troubleshooting support for techno platforms across MSAT to ensure business continuity (10%).
About you
Experience :
Must have a minimum of 4 years (PhD) or 7 years (MSc) of relevant process modelling/process diagnostics experience in manufacturing or industrial settings.
7 or more years of experience with increasing responsibilities in project and stakeholder management.
5+ years of experience in delivering insights through multivariate statistics, mathematical modelling, and data visualization.
Proficient in using classification, clustering, and dimensionality reduction.
Computer proficiency and experience with modelling software, coding languages and other tools
Strong knowledge in working with data historian systems, including PI Asset Framework (AF) & PI Event Frames, Manufacturing Execution System (MES) and IoT solutions.
Experience with implementing ETL processes for aggregating and contextualizing data.
Experience with developing business requirements, and ability to influence and communicate with a diverse group of stakeholders from multiple levels of management.
Ability to deliver projects with complex requirements and a strong customer focus.
Technical skills :
Data analysis and modelling using open-source software libraries, SIMCA, Dataiku and JMP
Database design/management tools: AVEVA PI or Aspen InfoPlus 21 historian, MS SQL Server, MySQL, and PostgreSQL
Scripting tools: Python, R, and SQL
Data visualization: Power BI, Streamlet, PI Vision
Big Data/cloud platforms: AWS, Snowflake, Azure
Other relevant software such as MS office, software for project management and agile activity tracking.
Project Management:
Lean & Agile practices
User experience management
Vendor management
Transversal Skills & Competencies (Soft skills):
Problem solving and decision making
Storytelling and technical writing
Building partnerships/stakeholder management
Transversal collaboration
Strategic thinking
Change management
Education :
MSc. or PhD in process, industrial or chemical engineering with data science or process