Pros
Good exposure to real-world R&D data problems, including building and supporting scientific applications that directly help researchers. Teams are collaborative, and there’s an emphasis on problem-solving rather than just following tickets. You’ll get to work closely with scientists and product owners, which is interesting compared to pure IT roles. Work–life balance is usually manageable, with reasonable deadlines and flexibility in working hours depending on the project phase. The tech stack is evolving — opportunities to work with Python, cloud platforms (AWS, Foundry, etc.), and data integration pipelines. A global setup: you’ll interact with colleagues in Europe and the US, which gives broader exposure.
Cons
Growth path and promotions can feel a bit slow — career progression depends a lot on your manager and business priorities. Some legacy systems and processes are still in place, which can slow down innovation or adoption of new technologies. Decision making can be slow due to multiple stakeholders in R&D and IT needing alignment. Training on domain knowledge is a bit limited; you need to self-learn a lot to keep up with scientists’ requirements. Compensation is decent but may not match some of the top pure-tech companies in Bangalore.
