Senior Data Scientist – Personalisation

InPost Group

Data Scientist leveraging analytics and machine learning to improve e-commerce operations at InPost. Collaborating with cross-functional teams to drive strategic decision-making and operational excellence.

Posted 6/20/2026full-timeRemote • 🇵🇱 PolandSeniorWebsite

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformNumpyPandasPySparkPythonPyTorchScikit-Learn

About the role

Key responsibilities & impact

Partner with our Product and Business Teams to understand their needs, translate them into data science solutions, and provide actionable insights.
Develop and implement data science solutions (ML models, GenAI products, hybrid approaches, data analytics) to optimize marketing and products strategies, enhance user experience and shape targeting.
Collaborate closely with cross-functional teams (e.g. other Data&AI teams, Technology teams) to ensure seamless integration of data-driven initiatives.
Stay ahead of the curve exploring cutting-edge methods and being on top of new trends in Data Science & AI.
Communicate insights and recommendations to the management and business teams, and other data community members.

Requirements

What you’ll need

Education – Bachelor’s or Master’s degree in a relevant field, e.g. Data Science, Computer Science, Mathematics, Econometrics
Experience – you have at least 3 years of commercial experience as a Data Scientist.
Consulting and marketing analytics experience are a plus
Mindset – you are goal-oriented and independent, skilled in change and time management, business-conscious, able to think long-term and decompose business problems
Languages – you are proficient in Polish and English (other languages knowledge is a plus).
Technical skills: Excellent knowledge of ML solutions and their impact on business and user experience (clustering, recommender systems, regression, classification, etc.).
Hands-on experience with working with large amounts of data.
Proficiency in Python 3, as well as ML and data analysis libraries (e.g. Pandas, Numpy, Scipy, Scikit-learn, Statsmodels, TF/Pytorch, etc.).
Experience in writing well-structured code: functions, classes, modules.
Knowledge and experience in PySpark, relational databases, cloud solutions (e.g. Databricks, Azure, GCP, AWS, Snowflake).
Nice to have: Experience in leveraging CI/CD pipelines in data-based products.
Experience with data pipelines framework, preferably Kedro.
Experience with CLI tools: bash/zsh.

Benefits

Comp & perks

Impact: Your work will directly influence strategic decisions and operational efficiencies across multiple international markets.
Innovation: Be part of the team that's pushing boundaries of data analytics, working with the latest technologies and methodologies.
Growth: This role offers unparalleled opportunities for professional development in a data-driven, technology-forward environment.
Collaboration: Engage with cross-functional teams, share knowledge and best practices, fostering a culture of continuous learning and improvement.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data sciencemachine learningdata analyticsclusteringrecommender systemsregressionclassificationPython 3PySparkdata pipelines

Soft Skills

goal-orientedindependentchange managementtime managementbusiness-consciouslong-term thinkingproblem decomposition