Sanofi Pasteur Limited
Reference #: R2578520
Position Title: Process Data Scientist – Vaccine
Department: Process Control Strategy and Statistical Analysis
Location: Sanofi Pasteur Limited, Toronto, Ontario
Sanofi Pasteur: The world’s leading vaccine company
Sanofi Pasteur, the vaccines division of Sanofi, is the largest company in the world devoted entirely to human vaccines. Our driving goal is to protect people from infectious diseases by creating safe and effective vaccines. Our company distributes more than 1 billion doses of vaccine each year, making it possible to vaccinate more than 500 million people across the globe. Sanofi Pasteur offers the broadest range of vaccines in the world, providing protection against 20 bacterial and viral diseases.
Sanofi is dedicated to supporting people through their health challenges. We are a global biopharmaceutical company focused on human health. We prevent illness with vaccines, provide innovative treatments to fight pain and ease suffering. We stand by the few who suffer from rare diseases and the millions with long-term chronic conditions. With more than 100,000 people in 100 countries, Sanofi is transforming scientific innovation into healthcare solutions around the globe.
- Partner with internal stakeholders from multiple departments to identify opportunity for applying data science to solve complex business challenges such as maximize yield, process robustness, predictable supply, proactive identification of potential issues.
- Extract, transform and analyze data from multiple data sources ensuring data quality and integrity is maintained from source to the final output.
- Develop and implement algorithms using advanced statistical and mathematical methods.
- Recommend and lead implementation of Process Analytical Technologies to enable data capture for use in quantitative analysis and improved level of process understanding.
- Provide clear and concise oral and written communication.
- Promote a strong quality mindset with a strong focus on data integrity, validation and data governance.
Education and Experience:
- MS or PhD in Process or Industrial Engineering
- Experience in data science, process modeling or a similar technical field
- Minimum 1- 3 years of relevant industrial experience
- Experience with MVDA (PCA/PLS), DOE, SPC and statistics
- Strong experience in delivering insights through statistical data analysis, data modeling and data visualization
- Experience using tools such as R, SAS JMP, Python, Matlab, KNIME, and SIMCA
- Experience with developing business requirements, use cases and user stories in a data analytics context
- Experience with implementing ETL processes for aggregating and contextualizing data
- Exposure to best practices in data management and data governance practices
- Ability to deliver projects with complex requirements and a strong customer focus
- Ability to influence and communicate with a diverse group of stakeholders from multiple levels of management
- Ability to succeed in a team-oriented environment under very dynamic conditions
- Experience with Industrial Internet of Things.
- Experience with Big Data ecosystem
Sanofi is an equal opportunity employer committed to diversity and inclusion. Our goal is to attract, develop and retain highly talented employees from diverse backgrounds, allowing us to benefit from a wide variety of experiences and perspectives. We welcome and encourage applications from all qualified applicants. Accommodations for persons with disabilities required during the recruitment process are available upon request.
Thank you in advance for your interest.
Only those candidates selected for interviews will be contacted.
Sanofi, Empowering Life
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.