Regulatory Digital Transformation & Data Co-Op

Bayer
Tulsa, Oklahoma, United StatesPosted Sep 1, 2026

About the role

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice. Regulatory Digital Transformation & Data Co-Op We are seeking a highly motivated Data Science, Data Engineering, Computer Science, or Information Systems student to partner with our Medical Device Regulatory Affairs organization. This role will focus on mapping, analyzing, and improving the interconnectedness of regulatory databases, document repositories, workflows, and digital tools used across the product lifecycle; the successful candidate will help identify opportunities to reduce manual work, improve data accessibility, increase regulatory process efficiency, and support the development of a connected regulatory information ecosystem; this is an excellent opportunity for a student interested in applying data science and digital transformation principles within a highly regulated healthcare and medical technology environment.

YOUR TASKS AND RESPONSIBILITIES

Inventory and document regulatory databases, repositories, dashboards, and software tools used across the Regulatory Affairs organization; Create current‑state process maps that illustrate how information flows between systems and identify duplicate data entry, disconnected workflows, and manual handoffs; Interview stakeholders across Regulatory Affairs, Quality, Clinical, R&D, and Operations to capture business processes, data needs, and pain points; Analyze relationships between systems, data sources, and business processes to evaluate op

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