Senior Data Scientist (f/m/d)

About Moss

Moss is a leading Finance AI platform serving Europe's mid-market companies, enabling real-time control and insight over expenditures. The platform automates processes such as card issuance, invoice management, and expense handling, reducing manual administrative burdens for finance and accounting teams. Founded in Berlin, Moss has garnered over €200 million funding and serves 5,000+ businesses, including notable clients like Flink, Schufa, Gusto, and Auto1. Operating across Germany, the Netherlands, the UK, and other European markets, Moss employs 300+ staff from more than 50 nationalities, fostering a dynamic and impactful culture focused on fast learning and rapid innovation.

Role Overview

The Data & AI division is expanding, and we seek an experienced senior or lead-level data scientist with practical expertise in large language model (LLM) applications and classical machine learning. This role demands ownership of complete LLM and ML projects—from problem identification and modeling through evaluation, deployment, and continuous refinement—to optimize core product workflows including invoice processing, approval matching, reconciliation, anomaly detection, and user assistance.

Key Responsibilities

• Manage end-to-end machine learning and LLM pipelines for tasks like data extraction, classification, anomaly detection, and recommendation generation.
• Establish rigorous evaluation and monitoring frameworks involving gold standards, automated testing, robustness verification, service level agreements (SLAs), and tracking of costs and latency.
• Collaborate with Platform and Data Engineering teams to deploy models into production environments and iteratively enhance them based on stakeholder feedback.

Candidate Profile

• Between 5 and over 10 years of hands-on experience in applied machine learning, with a track record of deploying production-grade models and systems.
• Practical knowledge of LLM applications and agent tools, including function calling, retrieval-augmented generation (RAG), structured output techniques, and safety guardrails within live production settings.
• Proficiency in Python and relevant ML libraries like scikit-learn, XGBoost, LightGBM, PyTorch, or TensorFlow, coupled with strong capabilities in experiment design and model evaluation.
• Strategic problem-solving skills that emphasize thorough comprehension of business challenges, sound hypothesis testing, root cause analysis, and prioritization to direct development towards valuable outcomes.
• Ability to independently drive projects from concept through to scalable, monitored, and maintainable production systems, balancing model efficacy with technical feasibility and ongoing iteration.

Work Culture and Benefits

• Competitive salary package complemented by equity participation.
• Modern, lively offices fostering collaboration with regular team breakfasts and demo sessions.
• Generous work-from-abroad policy allowing up to 20 days remote international work.
• An annual learning and development fund of €600 or £600, plus other localized benefits.

Note: The listed benefits are applicable to full-time team members; interns and working students receive customized packages. By applying, candidates acknowledge compliance with Moss’s Data Privacy Policy.