Data Scientist

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:

•  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.

•  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.

•  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:

•  develop and maintain ML models for forecasting short-term demand signals and detecting anomalies  across virtual warehouse clusters;

•  build predictive models to estimate task workload, execution times (ETA), and expected operational  performance;

•  design algorithms to optimize task distribution, sequencing, and prioritization across operational  teams;

•  develop routing and path-optimization models to improve picker movement efficiency within dark  stores;

•  construct data-driven decision modules that integrate commercial rules, operational constraints, and  geometric layouts;

•  translate business requirements into ML-supported decision flows and automate key parts of  operational logic;

•  build SQL pipelines and data transformations for commercial, operations, and logistics datasets;

•  work closely with supply chain, dark store operations, category management, and IT to deliver  measurable improvements;

•  conduct A/B testing, validate model impact, and ensure high-quality model monitoring.

Requirements:

•  bachelor's Degree in Mathematics / Quantitative Economics / Econometrics / Statistics / Computer  Sciences / Finance;

•  at least 2 years working experience on Data Science;

•  strong mathematical background in Linear algebra, Probability, Statistics & Optimization Techniques;

•  proven experience with SQL (Window functions, CTEs, joins) and Python;

•  expertise in Machine Learning, Time Series Analysis and application of Statistical Concepts  (Hypothesis testing, A/B tests, PCA);

•  ability to work independently and decompose complex problems.

Preferred:

•  experience with Airflow, Docker, or Kubernetes for Data Orchestration;

•  practical experience with Amazon SageMaker: training, deploying, and monitoring ML models in a  production environment;

•  knowledge of Reporting and Business Intelligence Software (Power BI, Tableau, Looker);

•  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;

•  сaring corporate culture;

•  a team where you can implement your ideas, experiment, and feel like you are among friends.