Senior Data Scientist (f/m/d)

Moss; Berlin; Vor Ort; EUR 80.000 - 110.000; Vollzeit

Benefits dieser Stelle

Equity

20 days 'work from abroad'

€600 Learning & Development Budget

Zusammenfassung

Moss in Berlin is expanding its Data & AI team and seeking a Senior Machine Learning Engineer with hands-on LLM experience. You will own LLM/ML initiatives that directly enhance core product workflows including anomaly detection and user assistance.

The ideal candidate has 5-10+ years in applied ML, strong Python skills, and the ability to lead projects from ideation to production. Additional benefits include a comprehensive compensation package including equity and learning budgets.

Qualifikationen

• 5‑10+ years in applied ML with production ownership of shipping models/systems.
• Experience defining evaluation & monitoring processes: gold sets, automated tests, robustness checks.
• Ability to productionise models and iteratively improve them.

Aufgaben

• Own LLM/ML pipelines for extraction, classification, anomaly detection, and recommendations.
• Define evaluation & monitoring including cost/latency tracking.
• Collaborate with Platform/Data Engineering to bring models live.

Kenntnisse

Hands-on LLM app/agent experience

Python and ML stack (scikit-learn, XGBoost/LightGBM, PyTorch/TF)

Strong experiment/evaluation skills

Strategic Problem Solving

End-to-End project execution

Jobbeschreibung

At Moss, we give finance professionals the power to automate their day-to-day and make forward-thinking decisions.

Our team and culture make us unique — we’re driven by impact and growth, where every one of us strives to learn and excel. Recognized by Sifted’s Rising 100 and LinkedIn's Top Startups, we’re here to help propel your career and together, make Moss a lasting success.

We’re expanding our Data & AI team and looking for a senior/lead contributor who has hands‑on LLM app/agent experience and is fluent in classical ML. You’ll own end‑to‑end LLM/ML initiatives – from problem framing and modeling to evaluation, deployment, and iteration – directly improving core product workflows (invoice understanding, approval matching, reconciliation, anomaly detection, and user‑assist).

Your responsibilities

• Own LLM/ML pipelines for extraction, classification, anomaly detection, and recommendations.
• Define evaluation & monitoring: gold sets, automated tests, robustness checks, SLAs, and cost/latency tracking.
• Productionise with Platform/Data Eng: bring your models live and iterate/improve until they are adopted by your stakeholders.

About you

• 5‑10+ years in applied ML with production ownership of shipping models/systems.
• Hands‑on LLM app/agent experience (tool use/function calling, RAG, structured outputs, guardrails) in production.
• Strong Python + ML stack (e.g., scikit‑learn, XGBoost/LightGBM, PyTorch/TF) and solid experiment/evaluation skills.
• Strategic Problem Solver: You approach ambiguous problems by deeply understanding business context and framing data science solutions that drive meaningful outcomes. You rigorously validate assumptions, identify root causes, and prioritize solving the right problem before building.
• End‑to‑End Executor: You independently own projects from ideation to production, balancing model performance with engineering realities. You ensure solutions are scalable, monitored, and maintained with thoughtful evaluation, deployment, and iteration strategies.

About Moss

Moss is a SaaS scale‑up founded in Berlin, with a team of 300+ people from 50+ nationalities in 5 offices across Europe.

Moss has raised a total of €180 million in funding and is backed by renowned tech investors including Valar Ventures, Tiger Global, Global Founders Capital, Cherry Ventures and A‑Star.

What else to expect

• Top‑of‑market compensation package, including equity.
• Our vibrant offices are at the heart of our culture, where in‑person time fuels collaboration and connection over weekly breakfasts and Friday demos.
• Additional benefits include: 20 days “work from abroad”, €600/GBP Learning & Development Budget, and other local benefits.

Unless stated otherwise, benefits apply to full‑time positions (interns and working students receive a tailored package).

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