Senior Data Scientist - Personalisation (m/f/n)

Location: Pana Tadeusza, Kraków, Poland

Company

InPost operates an e-commerce parcel delivery and out-of-home logistics platform with automated parcel machines, pick-up and drop-off points, courier, and fulfilment services across Europe.

What you will do

• Partner with Product and Business teams to understand needs and translate them into data science solutions.
• Develop ML models, GenAI products, hybrid approaches, and analytical solutions for marketing, product strategy, targeting, and user experience.
• Work with products including InPost Mobile, the Loyalty Programme, and InPost Pay.
• Collaborate with Data & AI and Technology teams to integrate data-driven initiatives.
• Explore new Data Science and AI methods and communicate insights and recommendations to management and business stakeholders.
• Deliver data products end to end, including problem analysis, solution development, presentation, maintenance, and model monitoring.

Requirements

• Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Econometrics, or a related field.
• At least 3 years of commercial experience as a Data Scientist.
• Excellent knowledge of machine learning methods including clustering, recommender systems, regression, and classification.
• Hands-on experience working with large datasets and proficiency in Python, Pandas, NumPy, SciPy, Scikit-learn, Statsmodels, TensorFlow, or PyTorch.
• Experience writing well-structured code and working with PySpark, relational databases, and cloud solutions such as Databricks, Azure, GCP, AWS, or Snowflake.
• Proficiency in Polish and English is required. Strong communication, business awareness, independence, and problem-solving skills are expected.

Nice to have

• Consulting or marketing analytics experience.
• Experience with CI/CD pipelines in data products.
• Experience with data pipeline frameworks, preferably Kedro.
• Experience with CLI tools such as bash or zsh.

Culture & Benefits

• Work that influences strategic decisions and operational efficiency across multiple international markets.
• Exposure to modern data analytics technologies and methodologies.
• Opportunities for professional development in a data-driven technology environment.
• Cross-functional collaboration, knowledge sharing, and continuous learning.
• B2B contract.