Senior Data Scientist (f/m/d)

Moss
Berlin, Warsaw, Amsterdam
Workplace: HybridFull timeFunction: Data Science & Machine LearningExperience: 5-10 yearsSkills: ["Problem-solving","Strategic thinking","Validation","Ownership","Execution"]

Own end-to-end LLM/ML initiatives for core finance workflows, from problem framing and modeling to evaluation, deployment, and iteration. Build LLM/ML pipelines for extraction, classification, anomaly detection, and recommendations, and define evaluation/monitoring with gold sets, robustness checks, and cost/latency tracking. Partner with Platform/Data Engineering to productionize models and iterate until stakeholders adopt them across invoice understanding, matching, reconciliation, and user-assist.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Moss
Moss
2 months ago

Senior Data Scientist (f/m/d)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 17 hours agoStatus: Live

Job Summary

Own end-to-end LLM/ML initiatives for core finance workflows, from problem framing and modeling to evaluation, deployment, and iteration. Build LLM/ML pipelines for extraction, classification, anomaly detection, and recommendations, and define evaluation/monitoring with gold sets, robustness checks, and cost/latency tracking. Partner with Platform/Data Engineering to productionize models and iterate until stakeholders adopt them across invoice understanding, matching, reconciliation, and user-assist.
Location: Berlin, Warsaw, Amsterdam
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Sr. Manager level

Key Responsibilities

  • •Own LLM/ML pipelines for extraction, classification, anomaly detection, and recommendations.
  • •Define evaluation and monitoring, including gold sets, automated tests, robustness checks, SLAs, and cost/latency tracking.
  • •Productionize models with Platform/Data Engineering and iterate/improve until adopted by stakeholders.

Pay and Benefits

Perks:EquityLearning Budget

Key Requirements

  • •5-10+ years in applied ML with production ownership of shipping models/systems.
  • •Hands-on LLM app/agent experience in production, including tool use/function calling, RAG, structured outputs, and guardrails.
  • •Strong Python and ML stack experience (e.g., scikit-learn, XGBoost/LightGBM, PyTorch/TF) plus solid experiment and evaluation skills.
  • •Approach ambiguous problems by understanding business context, validating assumptions, identifying root causes, and prioritizing the right problem before building.
  • •Independently own projects from ideation to production, balancing model performance with engineering realities and maintaining scalable, monitored solutions.
Experience:5-10 yearsSaaS
Skills:Problem-solvingStrategic thinkingValidationOwnershipExecution
Tech Stack:PythonLLMRAGScikit-learnXGBoostLightGBMPyTorchTensorFlow

Company Brief

Moss
Berlin-based fintech providing spend management software, corporate cards, invoice and expense automation for SMEs and finance teams, enabling real-time control of company spending and integrations with accounting/ERP systems.
Industry: Fintech Infrastructure
Company Size: Large (251 to 1,000 employees)
Growth: Scaleup
Valuation: USD 500M to 1B
Funding: Series B
Headquarters: Berlin, Germany
Founded: 2019
Glassdoor
Glassdoor: 3.4
WebsiteLinkedInGlassdoor