Bayer seeks an incumbent who possesses the following: Required Skills and Experience: 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.); Familiarity or experience with cloud environments (e.g., AWS, GCP, Azure) preferred. The primary responsibilities of this role include: 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.