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(Senior) Data Scientist - Operations

Data Scientist • Senior • Hybrid • Full-time • Poland Kraków, Poland

InPost's Operations Data Science Team is looking for a data scientist to solve large-scale logistics problems. Your models won't sit in notebooks: they will move millions of parcels every day.

Responsibilities

  • ▹Design routing and allocation algorithms for parcel delivery
  • ▹Solve large-scale optimization problems (vehicles, routes, constraints, costs)
  • ▹Apply graph-based methods, clustering, regression and forecasting
  • ▹Build models that directly impact delivery speed, cost efficiency and customer experience
  • ▹Ship solutions into production, not just experiments

Requirements

  • ▹~3+ years in Data Science / ML roles
  • ▹Strong Python skills and experience with data/ML libraries (Pandas, NumPy, Scikit-learn, PyTorch / TensorFlow)
  • ▹Experience working with large-scale datasets
  • ▹Solid understanding of ML methods (regression, clustering, forecasting, etc.)
  • ▹Ability to translate business problems into data solutions

Nice to have

  • ▹Experience with optimization problems (routing, scheduling, operations research)
  • ▹Knowledge of graph-based approaches or network problems
  • ▹Models built and used in production at scale
  • ▹Experience with PySpark / cloud (Databricks, GCP, AWS, Snowflake)
  • ▹Experience with MLOps / CI/CD pipelines
  • ▹Familiarity with optimization techniques (linear programming, heuristics)
  • ▹Familiarity with Kedro or similar frameworks

Soft skills

Complex problem-solvingComfort working with messy real-world systems

What we offer

  • ▹Diverse, international, cross-functional environment with leading experts
  • ▹Learning from a senior leader and their leadership team in e-commerce and logistics
  • ▹Growing opportunities in several European locations
  • ▹Range of benefits and training opportunities
  • ▹Flexible hours
  • ▹B2B contract

About the company

InPost revolutionised e-commerce parcel delivery in Poland and is now one of Europe's leading out-of-home e-commerce enablement platforms, with almost 47,000 parcel machines and almost 35,000 pick-up drop-off points in nine countries.

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