Senior Data Scientist
Berlin, Germany
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingDevelop algorithms that extract actionable insights from AI search behavior, creating data-driven recommendations that help brands increase their AI Search visibility
Own the full model lifecycle from experimentation to production deployment, working closely with engineering to integrate ML solutions into our systems
Design and implement data pipelines to ingest, process, and analyze large volumes of data
From the employer’s posting
Train, test, and ship models that power Peec AI’s recommendations - helping customers boost their visibility in AI search Develop algorithms that extract actionable insights from AI search behavior, creating data-driven recommendations that help brands increase their AI Search visibility Own the full model lifecycle from experimentation to production deployment, working closely with engineering to integrate ML solutions into our systems
Develop algorithms that extract actionable insights from AI search behavior, creating data-driven recommendations that help brands increase their AI Search visibility Own the full model lifecycle from experimentation to production deployment, working closely with engineering to integrate ML solutions into our systems Design and implement data pipelines to ingest, process, and analyze large volumes of data
Own the full model lifecycle from experimentation to production deployment, working closely with engineering to integrate ML solutions into our systems Design and implement data pipelines to ingest, process, and analyze large volumes of data What we’re looking for
Tools in this posting
- Python
- Docker
- Google Cloud (GCP)
- Fastapi
- Huggingface
- NumPy
- pandas
- PyTorch
- TensorFlow
- SQL
- TypeScript
- BigQuery
- PostgreSQL
Source — Tool mentions in context
What we’re looking for - Proven backend development skills in Python with experience building APIs, data pipelines, or ML infrastructure, and familiarity with tools like FastAPI, Docker, and cloud platforms (preferably GCP) - Deep curiosity about how LLMs work, with the ability to reverse-engineer AI search behavior and translate patterns into actionable product features
Our Data Science Stack - Languages: Python, SQL - Libraries: Pandas, NumPy, HuggingFace, PyTorch, TensorFlow, ONNX
- Libraries: Pandas, NumPy, HuggingFace, PyTorch, TensorFlow, ONNX - Backend: GCP, Cloud Functions, Firestore, Postgres, AlloyDB, BigQuery - AI Models: OpenAI, Claude, Perplexity, Gemini, Llama, etc.
- Languages: Python, SQL - Libraries: Pandas, NumPy, HuggingFace, PyTorch, TensorFlow, ONNX - Backend: GCP, Cloud Functions, Firestore, Postgres, AlloyDB, BigQuery
- Having started a company before or worked at a high-growth startup - Fluency in Typescript What we offer
About Peec
Peec AI is the analytics platform for AI search.
In the employer’s words · Read in context
Job description
About Peec AI
Peec AI is the analytics platform for AI search. People increasingly discover products and make buying decisions through ChatGPT, Claude, Gemini, and Google's AI Overviews instead of traditional search, and most brands have no idea where they show up in those answers. Peec gives marketing, SEO, and growth teams the data to see exactly that: how visible their brand is across AI platforms, how they compare to competitors, and where to win.
We are defining this category, and the market is moving with us. Peec is a Series A company backed by 20VC and Singular, that went from $0 to $15M ARR in 18 months, with a 100+ person team across our Berlin HQ and our New York office.
What you’ll do
Train, test, and ship models that power Peec AI’s recommendations - helping customers boost their visibility in AI search
Develop algorithms that extract actionable insights from AI search behavior, creating data-driven recommendations that help brands increase their AI Search visibility
Own the full model lifecycle from experimentation to production deployment, working closely with engineering to integrate ML solutions into our systems
Design and implement data pipelines to ingest, process, and analyze large volumes of data
What we’re looking for
Proven backend development skills in Python with experience building APIs, data pipelines, or ML infrastructure, and familiarity with tools like FastAPI, Docker, and cloud platforms (preferably GCP)
Deep curiosity about how LLMs work, with the ability to reverse-engineer AI search behavior and translate patterns into actionable product features
Track record of taking projects from research to production in a fast-moving startup environment, with strong problem-solving skills and comfort working with ambiguous, evolving problems
Excellent communication skills with the ability to explain complex technical concepts to customers and stakeholders
Our Data Science Stack
Languages: Python, SQL
Libraries: Pandas, NumPy, HuggingFace, PyTorch, TensorFlow, ONNX
Backend: GCP, Cloud Functions, Firestore, Postgres, AlloyDB, BigQuery
AI Models: OpenAI, Claude, Perplexity, Gemini, Llama, etc.
Bonus Points
Contributions to open-source projects
Deployed side/hobby projects that we can check out
Presented research papers at top ML or AI conferences
Having started a company before or worked at a high-growth startup
Fluency in Typescript
What we offer
Exciting and challenging work with real impact and ownership at one of Europe’s fastest-growing Series A startups
Regular team events and off-sites
Aggressive equity compensation package
Paid Dinner & Uber home when working late
The most beautiful office space and work environment in Berlin
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
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Source & posting history
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Berlin, Germany
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Jun 26, 2026
- Recorded sightings
- 70
- Last seen by us
- Oct 8, 2026
- Employer says posted
- Jun 24, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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