Trade RepublicData Scientist – Berlin
Trade Republic is hiring a Data Scientist – Berlin (Germany). Level rates it ; you can apply on Level.
AI in this role
BEST WORK OF YOUR CAREER
Trade Republic is the largest savings platform in Europe - we operate in 17 countries, serving +10 million customers who trusted us with over 100B in assets. But we’re striving for more.
We have a bold mission to empower everyone to build wealth with easy, safe, and free access to financial systems. You will have the opportunity to grow your career by collaborating with a team of outstanding talents and state of the art technology to build a lasting, positive future for millions.
WHAT YOU'LL BE DOING
Our Operations Platform team leads the development of automated workflows and tools for our Operations and Customer Support staff to achieve an amazing customer experience.
To achieve this, we recognise that data isn't just a resource - it's a cornerstone. In this role you will:
- Plan and execute the roadmap for your services together with the team
- Play a pivotal role in designing the architecture of your data products, ensuring they are scalable, robust, and synergistic with our existing platforms
- Research, build, test and deploy models - this is where you will spend most of your time. With a focus on team ownership, this gives a lot of time for our developers and data scientists to actually work technically instead of with process
- Once deployed, you will continue to oversee your products, monitoring their performance metrics and making data-driven adjustments as needed to optimise result
WHAT WE'RE LOOKING FOR
- at least 5 years of end-to-end data science and software engineering experience, preferably in a dynamic environment with a modern tech stack
- Experience working in Operations, specifically significant experience in customer service automations
- Experience with applying a wide variety of machine learning techniques to business problems, particularly with tabular and natural language data
- Strong command of SQL, Python together with its scientific stack (numpy, pandas, matplotlib, scikit-learn)
- Good understanding of Software Engineering practices (e.g. test-driven development, OOP, CI/CD, etc.) and experience with productionizing ML products
- Recent hands-on experience in deploying and maintaining an AI agent/workflow powered by LLMs, using both low level SDKs (openai, anthropic, google-genai,..) and prompt engineering frameworks (llama-index, langchain, dspy, ..)
- General understanding of LLMOps principles, for evaluating, testing, versioning and experimenting prompts in staging and production (langsmith, langfuse, arize-phoenix, lunary, ..)
WHY YOU SHOULD APPLY NOW
Our culture rewards ownership, excellence, and high energy. We care deeply about outcomes and hold each other accountable - we’re here to win and fix one of the largest challenges Europeans face - closing the pension gap and democratising wealth. If this gets you fired up, reach out!
We believe it’s our team’s varied identities and backgrounds that make us sharper and stronger. We’re committed to creating an environment where everyone feels respected and has equal opportunity to thrive in their careers. For any questions on DEI during the interview process, reach out to your recruitment partner.
How we rate this
Data Scientist – Berlin at Trade Republic rates 83 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- What are the limits of OpenAI that you've run into, and how did you work around them?
- What's a project where you used Anthropic hands-on?
- Walk me through how you've used Llama in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Prompt engineering, AI agents, OpenAI, Anthropic, and Llama. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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