From data scientist to a new role ?
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Hi everyone,<\/p>\n
I\u2019m 25, currently working as a Data Scientist & AI Engineer at a large Space company in Europe, with ~2.5 years of experience. My focus has been on LLM R&D, RAG pipelines, satellite telemetry anomaly detection, surrogate modeling, and some FPGA-compatible ML for onboard systems. I also mentor interns, coordinate small R&D projects, and occasionally present findings internally.<\/p>\n
The context is tough (departures, headcount freezes) and I have an opportunity to move to a large aeronautics company or stay in my team, but grow in scope.<\/p>\n
I\u2019m now evaluating two potential next roles (which I might intend as ~2-year commitments before moving on) and would love advice from anyone who has experience with either path:<\/p>\n
\u2e3b<\/p>\n
Option 1 \u2013 AI Product Manager \/ Project Manager in HR<\/p>\n
\u2022 Deploy 8 AI agents across HR services, impacting ~130k employees. \u2022 Lead roadmap, orchestrate AI integrations, and liaise with IT and HR VPs. \u2022 Focus on coordination, strategy, and high-level product ownership. \u2022 Access to cutting-edge generative AI tools and cloud-based agentic workflows. \u2022 High exposure to senior stakeholders and leadership opportunities. \u2022 Some political stress: managing expectations of VPs, cross-team alignment, continuous meetings. It is said to be a quite political environment as you deal with HR and not just engineers. <\/code><\/pre>\n\u2e3b<\/p>\n
Option 2 \u2013 Big data product owner + AI R&D manager (Tech + Product Ownership) in Space<\/p>\n
\u2022 Merge internal Big Data platforms and integrate AI\/analytics pipelines and PO role for a 600 user data lake platform (on premise due to security constraints), coordinating subcontractors. \u2022 Manage R&D programs with subcontractors, support bids, and deploy ML models. \u2022 some Hands-on technical + coordination (MLops, RAG, keeping 1 data science R&D project as a IC and take subs for the rest), some product ownership. \u2022 Exposure mostly internal; less political stress, but operational and technical expectations remain high. \u2022 Technical constraints due to working in a defense context: access to cutting-edge AI tools is limited, and infrastructure is slower\/more constrained. \u2022 Opportunity to remain in the aerospace\/space field I\u2019m passionate about, but external market is niche. <\/code><\/pre>\n\u2e3b<\/p>\n
My Considerations<\/p>\n
\u2022 I\u2019m not an elite coder; my strength is prototyping, vision, and leadership rather than optimizing code. \u2022 Life-work balance is important; I do ~12\u201320h of meetings per week currently and enjoy running, cycling, and other hobbies. \u2022 Option 1 offers exposure to latest AI technologies and high-level leadership, but comes with political challenges. Also, HR tech is not sexy. \u2022 Option 2 is more technical and personally interesting (space), but tools and infrastructure are slower, and the field is more niche. Plus it\u2019s in a crisis in Europe meaning we could have 2-5 years of stagnation. <\/code><\/pre>\n\u2e3b<\/p>\n
Questions to the community:<\/p>\n
1. If you had to choose between strategic PM exposure with generative AI vs hands-on hybrid tech + product in a niche field, which would you pick early in your career? 2. Which path do you think gives the strongest leverage for leadership or high-profile opportunities? 3. Any advice on navigating political stress if I take the PM role? 4. Are there hybrid ways to make the PM role technically \u201csexier\u201d or future-proof in AI? 5. I am also considering moving into high paid remote roles such as tech sales in the future. Which would work as the best intermediate role ? <\/code><\/pre>\nThanks in advance for your insights! Any real-world experience, pros\/cons, or anecdotal advice is hugely appreciated.<\/p>\n<\/p><\/div>\n
submitted by \/u\/LocPat <\/a>
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