Trans.eu operates a transportation exchange connecting carriers, freight forwarders, and shippers across 12 European countries. The tech stack reveals a data-intensive operation: Node.js + TypeScript for backend services, PostgreSQL + Snowflake for analytics, and a heavy ML/AI layer (TensorFlow, PyTorch, scikit-learn, gradient boosting) focused on fraud detection, credit risk, and segmentation models. Project list confirms this shape — the company is mid-transformation, scaling feature stores and MLOps infrastructure while building an AI risk & compliance tier, signaling a shift from marketplace-as-utility toward embedded financial and operational intelligence for logistics.
Trans.eu Group operates a digital freight exchange and logistics platform serving the European road transport industry. The company connects carriers, freight forwarders, logistics centers, and shippers on a unified marketplace, supplemented by tools for business process optimization, cost reduction, and financial intelligence. Founded in 2004, the group employs approximately 1,000 people across 12 countries, with headquarters in Wrocław, Poland. Current hiring activity is concentrated in data roles (5 open positions) and engineering (3 roles), reflecting infrastructure scaling; overall hiring velocity is decelerating.
Backend: Node.js, TypeScript, NestJS, Go. Data: PostgreSQL, Redis, RabbitMQ, Snowflake, dbt. Deployment: Docker, Kubernetes, Terraform, AWS. ML/AI: TensorFlow, PyTorch, scikit-learn, XGBoost, LightGBM, Keras, CatBoost. Analytics: Tableau, Pandas, NumPy.
AI/ML infrastructure: fraud detection, credit risk assessment, AI risk & compliance models, feature stores, and LLM gateways. Analytics: advanced segmentation models, Tableau dashboards, enterprise data warehouse ETL/ELT solutions for machine learning.
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