Hello!
We are E-Com, a team of Foodtech and Ukrainian product lovers.
And we also break stereotypes that retail is only about tomatoes. Believe me, the technical part of our projects provides a whole field for creativity and brainstorming.
What we are currently working on:
- we are upgrading the existing delivery of a wide range of products from Silpo stores;
- we are developing super-fast delivery of products and dishes under the new LOKO brand.
We are developing a next-generation Decision Support Platform that connects demand planning, operational orchestration, and in-store execution optimization into one unified Analytics and Machine Learning Ecosystem.
The project focuses on three major streams:
β’ Demand & Forecasting Intelligence: building short-term demand forecasting models, generating granular demand signals for operational planning, identifying anomalies, and supporting commercial decision logic across virtual warehouse clusters.
β’ Operational Orchestration & Task Optimization: designing predictive models for workload estimation, task duration (ETA), and prioritization. Developing algorithms that automatically map operational needs into structured tasks and optimize their sequencing and allocation across teams.
β’ In-Store Execution & Routing Optimization: developing models that optimize picker movement, predict in-store congestion, and recommend optimal routes and execution flows. Integrating store layout geometry, product characteristics, and operational constraints to enhance dark-store efficiency.
You will join a cross-functional team to design and implement data-driven decision module that directly influence commercial and operational decisions.
Responsibilities:
β’ develop and maintain ML models for forecasting short-term demand signals and detecting anomalies across virtual warehouse clusters;
β’ build predictive models to estimate task workload, execution times (ETA), and expected operational performance;
β’ design algorithms to optimize task distribution, sequencing, and prioritization across operational teams;
β’ develop routing and path-optimization models to improve picker movement efficiency within dark stores;
β’ construct data-driven decision modules that integrate commercial rules, operational constraints, and geometric layouts;
β’ translate business requirements into ML-supported decision flows and automate key parts of operational logic;
β’ build SQL pipelines and data transformations for commercial, operations, and logistics datasets;
β’ work closely with supply chain, dark store operations, category management, and IT to deliver measurable improvements;
β’ conduct A/B testing, validate model impact, and ensure high-quality model monitoring.
Requirements:
β’ bachelorβs Degree in Mathematics / Quantitative Economics / Econometrics / Statistics / Computer Sciences / Finance;
β’ at least 2 years working experience on Data Science;
β’ strong mathematical background in Linear algebra, Probability, Statistics & Optimization Techniques;
β’ proven experience with SQL (Window functions, CTEs, joins) and Python;
β’ expertise in Machine Learning, Time Series Analysis and application of Statistical Concepts (Hypothesis testing, A/B tests, PCA);
β’ ability to work independently and decompose complex problems.
Preferred:
β’ experience with Airflow, Docker, or Kubernetes for Data Orchestration;
β’ practical experience with Amazon SageMaker: training, deploying, and monitoring ML models in a production environment;
β’ knowledge of Reporting and Business Intelligence Software (Power BI, Tableau, Looker);
β’ ability to design and deliver packaged analytical/ML solutions.
What we offer
- competitive salary;
- opportunity to work on flagship projects impacting millions of users;
- flexible remote or office-based work (with backup power and reliable connectivity at SilverBreeze Business Center);
- flexible working schedule;
- medical and Life insurance packages;
- support for GIG contract or private entrepreneurship arrangements;
- discounts at Fozzy Group stores and restaurants;
- psychological support services;
- Caring corporate culture;
- a team where you can implement your ideas, experiment, and feel like you are among friends.
