Data Scientist (вакансія неактивна)

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.