Kraków, Województwo małopolskie, Poland
Likely evergreen, first seen by us 74 days agoWork setup in the employer’s posting: RemoteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
~3+ years in Data Science / ML roles
Strong Python skills and experience with data/ML libraries
Solid understanding of ML methods (regression, clustering, forecasting, etc.)
Ability to translate business problems into data solutions
Likely evergreenReposted 2 times since May 13, 2026. A role that keeps coming back is often kept open to collect applications rather than to fill one seat.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
Day 74
Up longer than most. Similar jobs usually come down between day 7 and day 56.
Well past InPost’s usual: its jobs come down by about day 12.
From 10,380 similar postings that came down, and 49 of InPost’s. Coming down is not always a hire.
12 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- ~3+ years in Data Science / ML roles - Strong Python skills and experience with data/ML libraries - Experience working with large-scale datasets
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
- 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
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Yes. We’ve followed 3 other (Senior) Data Scientist - Operations (m/f/n) jobs there since May 2026. 3 came down, usually after about 20 days.
Large employers often post one title for several teams, so these can be separate openings.
New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Your work will include:
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:
You’ll stand out if you:
Why join InPost?
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
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Kraków, Województwo małopolskie, Poland
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.