Senior Data Scientist m/w/d
Core
Design, build, and maintain end-to-end ML pipelines for document extraction, classification, and data enrichment in production logistics systems.
Role type
Senior Data Scientist Engineer (Production ML Systems)
Builds
Production ML systems for document automation, demand forecasting, churn prediction, and route optimization
Domain
Logistics, Supply Chain, Freight Forwarding
Deliverable
production ML models
Required skills
Python, LLMs (prompting, fine-tuning, evaluation), classical data science (regression, classification, time series), ML pipeline architecture, monitoring, reliability engineering, agentic coding tools, statistics, hypothesis testing
Preferred skills
Logistics/supply chain domain experience, semantic similarity and entity resolution, human-in-the-loop workflows, demand forecasting, time series modeling, route/network optimization, low volume data handling
Technologies
LLMs, custom models, rule-based postprocessing, Python
Responsibilities
Design and maintain end-to-end ML pipelines for document extraction; Develop LLM-based extraction systems for logistics documents; Build prompt evaluation frameworks and feedback loops; Train custom in-house models using HITL data; Build semantic similarity models for vocabulary mapping; Contribute to rate sheet extraction logic; Improve pipeline reliability through testing and monitoring; Evaluate and introduce disruptive approaches for accuracy improvements; Scope and build predictive analytics workstreams; Partner with Product Managers to shape roadmaps; Collaborate with Engineering on integration and API design
Seniority
Senior, hands-on IC