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(Senior) Data Scientist - Personalisation at InPost. Location Information: Poland. Company Description. 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. . We are seeking talented and passionate . Data Scientists. to join our . Personalization Hub. . In this role, . you will leverage advanced analytical techniques and machine learning models to extract actionable insights from our complex data sets, driving strategic decision-making and operational excellence. . You will collaborate closely with cross-functional teams to develop innovative solutions that enhance our logistics operations, improve efficiency, and elevate the customer experience. . If you have specialized knowledge in user, product and/or marketing data science (or want to possess it) - we would very much like to meet you! :) . Job Description. On a daily basis you will: . Partner with our Product and Business Teams . to understand their needs, translate them into data science solutions, and provide actionable insights. . We work with all business products within InPost, e.g. InPost Mobile, Loyalty Programme, InPost Pay, among others. . 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.   . In summary . – you will have an opportunity to conduct end-to-end data products: exploring business needs (skills: understanding business, communication), analyze problems and propose thesis (data analytics), develop a solution (skills: hands-on ML/AI), present insights and results (skills: communication, translating technical stuff to non-technical people, ppt/BI), maintain the solution (skills: basic BI skills, model monitoring). . Qualifications. Job requirements: . 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.. Additional Information. Why join Us?. 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.