How do DS/ML/SWE teams collaborate at Nokia, and how much autonomy do co-op students typically get?
Neehanth M. asked a question to Rita L.
Hi Rita, I'm Neehanth, a Data Science MS student. I saw you balance academia (Assistant Professor) with industry (Data Scientist at Nokia). I've completed my MS this December and interested in understanding how research mindset translates to corporate ML work.
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- Category: Role, Role description
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Hi Neehanth!
Happy New Year and starting with a great question!
Collaboration between Data Science, Machine Learning, and Software Engineering teams is generally very seamless. Team members work closely together, regularly sharing knowledge and combining their different areas of expertise. In many cases, we also have cross-domain teams where DS, ML, and SWE skills are brought together to explore problems end-to-end and deliver integrated solutions.Co-op students are given a meaningful level of autonomy, appropriate to their experience, and it also depends on the program they enroll in. They are encouraged to take ownership of well-defined tasks or components, while still receiving close mentorship and support from more experienced team members. This balance allows them to learn quickly, contribute real value, and gradually build independence within the team.
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Thanks, and happy New Year to you too!
Love the cross-domain collaboration and the co-op model of owning well-defined components with mentorship, that’s exactly the environment I’m looking for.
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