I’m a Senior Data Scientist in Germany with a PhD in Physics and a high GPA. I’m in my mid-30s and have completed all the relevant Coursera courses.
My job mainly involves using Tableau for data visualization and writing SQL queries. Recently, I’ve started working on GenAI projects, but I’m still new to it.
I took this job during a difficult time, looking for something easier, but now I want more challenging opportunities. Job openings in my area are rare and highly competitive, which is frustrating.
I’ve had interviews for high-skill roles, but I struggle to highlight impressive achievements from the last three years. My experience with GenAI and NLP is new (about three months), and our team faces resource limits like small GPUs and insufficient data, making it hard to fully explore projects.
I feel stuck in less challenging roles, even though I know I can contribute to higher-level positions. In interviews, I also tend to be too honest about my coding time or NLP experience, which might not work in my favor.
Has anyone else faced this? Any advice on how to better present my skills in interviews without underselling myself?
You could work on personal projects that require “high skills” and highlight them instead if you are targeting jobs that require similar skills. You could focus on business wins and ROI when talking about work related achievements. Idea is to highlight your strengths, and not your perceived weaknesses, while being truthful during the interviews. No one will hold it against you that you acquired the necessary skills in your personal time as long as you can demonstrate how it transfers to solving their pain points.
Thanks, yeah, I feel like that’s the way to go. Eventhough I have the feeling that they want to hear that I applied the skills in a professional context. During my last interview the interviewe was like “we need someone with more experience in GenAi” and I was like “how would a candidate with more experience look like?”. She had a tough time asnwering that, but in the end it came down to the job description of the most recent job.
Titles and grades matter less after your first job. True research roles where you publish papers or create new models are rare. Most data scientists end up in data engineering or business analysis, focusing on making things work and providing reports to management.
It sounds like you’re on the right track with exploring GenAI. If you can show useful results, your employer might give you more room for research.
Looking at the job market is smart. Startups offer flexibility but can be intense. Larger companies might offer more resources, but you risk being stuck in a specific role.
Networking could help too. Consider local meetups, academic collaborations, or adjunct teaching roles at universities. You could also ask your company for an intern to work on research projects together.
