Data Scientist - Logistics AI & ML

Welcome to the Delivery Experience (DEX) Data Science team at Allegro, focused on developing data-driven products that optimize logistics processes, volume management, and delivery time prediction using Machine Learning, Operations Research, Google Cloud Platform, and advanced analytics. The team builds AI systems to optimize delivery costs and network efficiency, collaborating closely with product, engineering, and operations to run AI/ML systems in production.

• At least 2 years of experience building and deploying Machine Learning and Artificial Intelligence solutions in production.
• Deep understanding of AI/ML methods, including decision tree-based algorithms, time series models, and neural networks.
• Proficiency in Python and familiarity with AI/ML libraries such as pandas, scikit-learn, CatBoost, Optuna, Prophet, PyTorch, and LangGraph.
• Advanced knowledge of SQL.
• Ability to translate business problems into AI/ML challenges.
• Polish and English language skills at B2 level.
• Degree related to quantitative methods or statistical and mathematical modeling in fields such as Data Science, Mathematics, Physics, Econometrics, Computer Science, Engineering, or Logistics.

Nice to have:

• Experience with workflow orchestration and AI platforms including Airflow and Google Cloud Composer.
• Knowledge of Operations Research, Mathematical Optimization techniques (MILP), and Graph Analytics.
• Experience with geospatial data and relevant libraries (GeoPandas, H3).

• Create complex data models using machine learning, deep learning, time series forecasting, and survival models.
• Utilize mathematical optimization techniques (such as MILP and OR-Tools) to solve complex logistics problems.
• Design, develop, and maintain core AI/ML systems directly in production environments.
• Research new AI methodologies to innovate logistics solutions.
• Employ Python and advanced SQL to process, automate, and analyze large datasets.
• Collaborate with engineering teams to ensure availability, integrity, accuracy, and scalability of ML pipelines and workflow orchestrations.
• Translate business challenges and supply chain bottlenecks into AI/ML or optimization problems.
• Work effectively with DEX stakeholders throughout the AI/ML system lifecycle and share knowledge within the team.

Nice to have:

• Experience with workflow orchestration and AI platforms such as Airflow and Google Cloud Composer.
• Familiarity with Operations Research concepts, Mathematical Optimization (MILP), and Graph Analytics.
• Experience handling geospatial data and libraries like GeoPandas and H3.