Sanofi Group Process Data Engineer III in Framingham, Massachusetts
Process Data Engineer III
Summary of Purpose/Major Responsibilities:
The Process Data Analytics (PDA) team is part of the Manufacturing Science and Analytical Technologies (MSAT) global function. The PDA team is responsible to obtain process data by connecting to a variety of source data systems and compiling the data into contextualized data sets in order to support process monitoring and key process-related decisions. This includes developing, implementing, and maintaining the necessary databases and applications.
The Process Data Engineer III interacts with a multitude of key stakeholders to identify and deliver on a diverse set of business use cases. Examples include configuring process data analytics for new or transferred products; developing new applications; contributing to the enterprise program to shift to a cloud-based infrastructure; and using advanced analytics (e.g. machine learning and digital twins) to identify key drivers of process performance. The preferred candidate will bring a balance of process experience and computer science skillset. GMP experience is a plus, but not required.
Review manufacturing processes and/or development and production data
Ensures the data analytics system operates in its validated state and consistently meets stakeholder needs
Develop code for cloud-based applications
Manipulate large data sets and use them to identify trends and reach meaningful conclusions
Lead small technical project teams and implement project plans.
Demonstrates solid understanding and use of engineering principles and practices to solve a range of complex problems in creative and practical ways.
Maintains and demonstrates knowledge of state-of-the-art principles and theories in their area of responsibility.
Provides technical guidance and trains less experienced staff. Interacts with colleagues from various functions such as Engineering, Manufacturing, Quality and IT Departments to coordinate the progression of projects and continuous improvement.
Bachelor’s degree in engineering or computer science with 5 years of experience
Master’s degree in engineering or computer science with 3 years of experience
Ph.D. in engineering or computer science.
Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.)
Experience with deep data analysis
Experience in biotechnology or the pharmaceutical industry
Experience with root cause analysis and/or risk assessment
Experience working with statistical analysis software (JMP, MatLab, etc.)
Experience with project leadership
Experience providing solutions for difficult technical issues
Experience communicating with senior management
Strong technical writing and communication skills
Experience communicating with cross-functional teams
Proficient in Microsoft Word, Excel, PowerPoint
Sanofi Inc. and its U.S. affiliates are Equal Opportunity and Affirmative Action employers committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race; color; creed; religion; national origin; age; ancestry; nationality; marital, domestic partnership or civil union status; sex, gender, gender identity or expression; affectional or sexual orientation; disability; veteran or military status or liability for military status; domestic violence victim status; atypical cellular or blood trait; genetic information (including the refusal to submit to genetic testing) or any other characteristic protected by law.
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.