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

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 a 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.

General requirements:

• Bachelor’s, Master’s or PhD degree in a relevant field such as data science, computer science, mathematics, statistics, econometrics, physics or similar.
• At least 3 years of experience working using data science methods.
• Data-driven, goal-oriented, proactive mindset; skilled in change and time management; business-conscious; able to think long-term and decompose business problems.
• Proficient in English and Polish.

Technical requirements:

• Excellent knowledge of ML solutions and their impact on business, user experience, and operational processes (supervised and unsupervised learning, clustering, recommender systems, regression, classification, linear programming, reinforcement learning, time series, geospatial analysis).
• Hands-on experience working with large amounts of data.
• Proficiency in Python 3 and ML/data analysis libraries (Pandas, Numpy, Scipy, Scikit-learn, Statsmodels, TensorFlow/PyTorch).
• Experience writing well-structured code: functions, classes, modules.
• Knowledge and experience with PySpark, relational databases, and cloud solutions (Databricks, Azure, GCP, AWS, Snowflake).

Nice to have:

• Proficiency in testing code.
• Knowledge of best practices for readable code, technical reviews, and maintainability.
• Knowledge of ML Ops and experience with data pipelines framework, preferably Kedro.
• Experience creating ML models used in production and knowledge of SRE principles.
• Experience with CLI tools: bash/zsh.
• Experience leveraging CI/CD pipelines in data-based products.
• Experience applying data science methods at scale or building models used in production by many users.
• Previous work on open-source projects.
• Experience working in a data-driven environment, designing, executing, and analysing many experiments.

• Partner with Product and Business Teams to understand their needs, translate them into data science solutions, and provide actionable insights.
• Develop and implement advanced data science solutions including ML models, AI products, and optimization frameworks.
• Collaborate closely with cross-functional teams to ensure seamless integration of data-driven initiatives.
• Stay ahead of new trends in Data Science and AI.
• Communicate insights and recommendations to management, business teams, and data community members.