Chemical Engineering Co-Op

Bayer•Chesterfield, MO

12h•Onsite

About The Position

In this co‑op role, you will integrate and develop workflows for data analysis applications, evaluate machine learning and advanced statistical methods, and explore their applications in the biopharmaceutical industry to support process understanding, monitoring, and optimization in process development and GMP manufacturing environments. Co-op Program Dates: Spring Co-op: January 11, 2027 – June 11, 2027 Fall Co-op: May 17, 2027 or June 14, 2027 – December 10, 2027

Requirements

Currently enrolled in a PhD program with a preferred focus in Engineering, Computer Science, Applied Math, or (Bio)Statistics
Undergraduate degree in Engineering, Computer Science, Applied Math, or (Bio)Statistics
Strong verbal and written communication skills
Ability to deal professionally with internal customers of various organizational levels
Ability to work effectively within the team and cross‑functionally
Good organization, documentation, prioritization, and scheduling skills, together with an overall desire to learn
Strong problem‑solving skills and critical thinking
Ability to learn new technical topics
Ability to work independently and multi‑task
Interest in machine learning applications (some experience is preferred)
Programming experience in multiple languages/environments (such as Python, R, etc.)

Nice To Haves

Familiarity or experience with cloud environments (e.g., AWS, GCP, Azure) preferred

Responsibilities

Develop, test, and document software applications and methods to increase the efficiency of advanced data analytics applications in the biotechnology industry
Use machine learning and advanced statistical methods to support process understanding, monitoring, and optimization
Develop data analysis applications and workflows for mining, pre‑processing, and visualization of data
Develop code in multiple programming languages (e.g., Python, R, etc.)
Support mining of process data from IT systems and databases
Evaluate and apply different machine learning and advanced statistical methods
Interact with data scientists to support activities and projects in the areas of bioprocess monitoring, root cause analysis, process understanding, and process improvements
Communicate the outcome of development activities to the team
Document project outcomes in a short technical report