Data Scientist - Logistics AI & ML @ Allegro sp. z o.o.

Allegro sp. z o.o.

Warszawa

On-site

PLN 163,000 - 232,000

Full time

14 days+

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Benefits offered by this job

English classes

Private healthcare

Training budget

Sport subscription

Bike parking

Canteen

Free beverages

Playroom

Job summary

Allegro sp. z o.o. in Warsaw is seeking a skilled Data Scientist to build ML/AI solutions deployed in production, focusing on decision trees, time series, and neural networks.

You will translate business challenges into AI problems and collaborate with product, engineering, and ops teams. We expect at least 2 years of hands-on experience, strong Python proficiency, and in-depth knowledge of Pandas/Polars, Scikit-learn, CatBoost, Optuna, Prophet, PyTorch, LangGraph, and SQL.

Qualifications

Must have at least 2 years of hands-on experience building ML/AI solutions in production.
Deep understanding of AI/ML methods including decision trees, time series models, and neural networks.
Strong Python programming skills and fluency with core AI/ML libraries (Pandas/Polars, Scikit-learn, CatBoost, Optuna, Prophet, PyTorch, LangGraph).
Advanced SQL skills and ability to translate business problems into AI/ML solutions.

Skills

Python

SQL

Polish (B2)

English (B2)

Analytical thinking

Experience: 2+ years ML in production

Education

Data Science / Mathematics / Physics / Econometrics / CS / Engineering / Logistics

Tools

Pandas/Polars

Scikit-learn

CatBoost

Optuna

Prophet

PyTorch

LangGraph

Airflow

Google Cloud Composer

Gemini Enterprise Platform (Vertex AI)

GeoPandas

Job description

We are looking for people who:

Experience: Have at least 2 years of experience in building Machine Learning and Artificial Intelligence solutions deployed in production.
AI/ML Knowledge: A deep understanding of AI/ML methods, especially decision tree-based algorithms, time series models, and neural networks.
Programming & Tools: Proficient in Python and highly comfortable with software development tools. Experience with core AI/ML Python libraries: Pandas/Polars, Scikit-learn, CatBoost, Optuna, Prophet, PyTorch, and LangGraph.
Databases: Advanced knowledge of SQL.
Analytical Thinking: Ability to translate business challenges into AI/ML problems and tackle them using novel approaches.
Languages: Polish B2 and English B2.
Education: Graduated with a degree strongly related to quantitative methods or statistical & mathematical modeling, such as Data Science, Mathematics, Physics, Econometrics, Computer Science, Engineering, Logistics, or a similar major.

Nice to have:

Proficiency in workflow orchestration and AI platforms, including Airflow / Google Cloud Composer and Gemini Enterprise Agent Platform (Vertex AI).
Familiarity with Operations Research concepts, Mathematical Optimization techniques (like MILP), and Graph Analytics.
Experience with geospatial data and relevant libraries (e.g., GeoPandas, H3).

Welcome to the Delivery Experience (DEX) Data Science team, where we pride ourselves on developing data-driven products that propel the business and logistics of Allegro forward. Our expertise spans across a wide range of logistics process optimization, volume management, and delivery time prediction. We utilize a mix of Machine Learning (ML), Operations Research optimization tools, Google Cloud Platform components, and advanced data analytics to solve complex business challenges.

We are building core Artificial Intelligence systems that dynamically optimize delivery costs and improve the efficiency of our network - including parcel lockers (One Box) and courier operations. Joining us means becoming part of a Data Science group that collaborates closely with product, engineering, and operations to build AI/ML systems running directly in production environments.

Important things for you:

The salary range for this position depending on the skill set is as follows (contract of employment, tax-deductible cost):
- PLN 14 600 - 20 825
- Annual bonus based on your annual performance and company results.
Our team is based in Warsaw.

Why is it worth working with us?

Data-Driven Impact: Data Science plays a key role at Allegro. Our models and analyses significantly optimize logistics operations, lowering costs and shortening delivery times on one of the world's largest e-commerce platforms.
Innovation: Direct involvement in building optimization solutions that revolutionize the logistics network and last-mile processes.
Skill Development: You will work alongside top specialists, gaining access to large-scale data sets and a modern technology stack on GCP.
Proven Solutions: Our solutions aren't just theoretical. They demonstrate effectiveness and performance in real-world production environments, handling real logistics conditions and massive e-commerce scale.

What's in it for you:

Flexible working hours in the hybrid model (4 days in the office / 1 day remote) - working hours start between 7:00 a.m. and 10:00 a.m. We also have 30 days of occasional remote work.
Annual bonus based on your annual performance and company results.
Well-located offices (with e.g. fully equipped kitchens, bicycle parking, terraces full of greenery) and excellent work tools (e.g., raised desks, ergonomic chairs, interactive conference rooms).
A 16" or 14" MacBook Pro or corresponding Dell with Windows (if you don't like Macs) and all the necessary accessories.
A wide selection of fringe benefits in a cafeteria plan - you choose what you like (e.g., medical, sports or lunch packages, insurance, purchase vouchers).
English classes that we pay for related to the specific nature of your job.
A training budget, inter-team tourism (see more here), hackathons, and an internal learning platform where you will find multiple trainings.
An additional day off for volunteering, which you can use alone, with a team, or with a larger group of people connected by a common goal.
Social events for Allegro people - Spin Kilometers, Family Day, Fat Thursday, Advent of Code, and many other occasions we enjoy.

#goodtobehere means that:

Data Modeling & Analysis: Creating complex data models using machine learning, deep learning, time series forecasting, and survival models.
Operations Research & Optimization: Utilizing mathematical optimization techniques (such as MILP and OR-Tools) to solve complex logistics problems.
AI System Development & Innovation: Designing, developing, and maintaining core AI/ML systems directly in production environments, as well as researching new AI methodologies.
Data Processing & Automation: Employing Python and advanced SQL to process, automate, and analyze large datasets, ensuring high-quality input data.
Data Management & Pipeline Reliability: Collaborating closely with engineering teams to foster the availability, integrity, accuracy, and scalability of ML pipelines and workflow orchestrations.
Research & Problem-Solving: Translating complex business challenges and supply chain bottlenecks into AI/ML or optimization problems, proactively testing novel approaches to minimize costs.
Collaboration & Communication: Working effectively with numerous DEX stakeholders throughout the full lifecycle of AI/ML systems, providing clear communication of advanced insights, and fostering knowledge sharing within the team.

Requirements: