Applying graph-based methods, clustering, regression and forecasting
Building models that directly impact delivery speed, cost efficiency and customer experience
Shipping solutions into production - not just experiments
What we’re looking for:
We don’t expect you to tick every box - but you should feel comfortable with complex problem-solving and working with messy real-world systems.
Must have:
~3+ years in Data Science / ML roles
Strong Python skills and experience with data/ML libraries
Experience working with large-scale datasets
Solid understanding of ML methods (regression, clustering, forecasting, etc.)
Ability to translate business problems into data solutions
You’ll stand out if you:
Have worked on optimization problems (routing, scheduling, operations research)
Know graph-based approaches or network problems
Have built models that are used in production at scale
Have experience with PySpark / cloud (Databricks, GCP, AWS, Snowflake)
Have experience with ML Ops / CI/CD pipelines
Are familiar with optimization techniques (linear programming, heuristics)
Are familiar with Kedro or similar frameworks
Why join InPost ?
Opportunity to work in a diverse , international , and cross-functional environment, along with leading experts .
You work and learn from a senior leader and their leadership team, expanding your experience and exposure in the e-commerce and logistics industries.
InPost is a growing company that offers its people an increasing number of opportunities in several locations in Europe.
Fulfilling careers with a range of benefits and investing in providing training opportunities for people development.
You will feel a part of the InPost community that makes an impact on sustainability, convenient deliveries, and the circular economy every day.
Excellent working environment and flexible hours
We offer B2B type of contract
InPost has revolutionised e-commerce parcel delivery in Poland and is now one of Europe’s leading OOH e-commerce enablement platforms. Founded in 1999 by Rafał Brzoska, InPost provides delivery services through our network of almost 47,000 Automated Parcel Machines (APMs) and almost 35,000 pick-up drop-off points (PUDO) in nine countries across Europe , as well as to-door courier and fulfilment services to e-commerce merchants. InPost ’s lockers provide consumers with a cheaper and more flexible, convenient, environmentally friendly and contactless delivery option.
You’ll join our Operations Data Science Team , solving some of the most complex and impactful logistics problems at scale. Your models won’t sit in notebooks - they will move millions of parcels every day!
Tech stack: Python (Pandas, NumPy, Scikit-learn, PyTorch / TensorFlow), PySpark & distributed processing, Cloud platforms (Azure / GCP / AWS). Databricks, SQL & data warehouses Originally posted on Himalayas
