About us
Fozzy Group is one of the largest trade industrial groups in Ukraine and one of the leading Ukrainian retailers,
with over 700 outlets all around the country. It is also engaged in e-commerce, food processing & production,
agricultural business, parcel delivery, logistics and banking.
Since its inception in 1997, Fozzy Group has focused on making innovative business improvements, creating
new opportunities for the market and further developing the industry as a whole.
Job Description:
The Foodtech team is looking for a Data Scientist to develop the Operational Analytics function for a fast[1]growing food delivery business. In this role, you will focus on time series forecasting, regression modeling,
simulation modeling, and end-to-end machine learning pipelines to support resource planning and
operational decision-making.
You will be responsible for developing simulation-based models that serve as a foundation for a digital twin
of operational processes, enabling scenario analysis, stress testing, and what-if simulations for capacity
planning and operational optimization.
You will work closely with product, engineering, and operations teams to transform data into measurable
business impact through production-ready ML and simulation solutions.
Job Responsibilities
β’ Develop and implement time series forecasting models for resource planning (demand, capacity,
couriers, delivery slots, operational load);
β’ Build regression and machine learning models to explain key drivers and support operational
decisions;
β’ Apply a wide range of time series approaches from classical models (SARIMA, ETS, Prophet) and
ML models (GB) to modern Deep Learning models (LSTM, Temporal CNNs, Transformers for TS);
β’ Design, build, and maintain end-to-end automated ML pipelines, deploy and operate models in
production using AWS SageMaker;
β’ Orchestrate training and inference workflows with Apache Airflow;
β’ Analyze large-scale operational datasets and convert results into insights, forecasts, and actionable
recommendations;
β’ Collaborate with product managers, engineers, and operations teams to define business problems
and validate analytical solutions;
β’ Monitor model performance, forecast stability, and business impact over time.
Requirements
β’ Bachelorβs Degree in Mathematics / Engineering / Computer Sciences / Quantitative Economics /
Econometrics;
β’ Strong mathematical background in Linear algebra, Probability, Statistics & Optimization Techniques;
β’ At least 2 years working experience on Data Science;
β’ Experience of the full cycle of model implementation (data collection, model training and evaluation,
model deployment and monitoring);
β’ Ability to work independently, proactively, and to decompose complex problems into actionable tasks.
Skills
Must Have
β’ Strong proficiency in Python with solid application of object-oriented programming (OOP) principles
(modular design, reusable components, maintainable code);
β’ Solid experience in time series forecasting and regression modeling;
β’ Practical knowledge of:
o Classical and ML forecasting techniques;
o Statistical methods (hypothesis testing, confidence intervals, A/B testing);
β’ Advanced SQL skills (window functions, complex queries);
β’ Experience building automated ML pipelines;
β’ Understanding of MLOps principles (model versioning, monitoring, CI/CD for ML).
Preferred
β’ Hands-on experience with AWS SageMaker (training jobs, endpoints, model registry);
β’ Experience with Apache Airflow for data and ML workflow orchestration;
β’ Knowledge of Reporting and Business Intelligence Software (Power BI, Tableau);
β’ Experience working with large-scale production data systems.
What We Offer
β’ Competitive salary;
β’ Professional & personal development opportunities;
β’ Being part of dynamic team of young & ambitious professionals;
β’ Corporate discounts for sport clubs and language courses;
β’ Medical insurance package
