Lead Data Scientist in Comfy

COMFY is a leading omnichannel retailer of household appliances and electronics in Ukraine with 110 stores, which is among the top three e-commerce platforms.

We are looking for a Lead Data Scientist for whom it is not enough to simply build models. This role is about the ability toown the full cycle of transforming data into solutions—from setting a problem to influencing the company's financial results.

The models here are not "for presentations" but are sewn into real business processes: pricing, promotions, inventory, assortment, personalization.

What makes this role particularly interesting:

• real scale - millions of transactions, complex seasonal patterns, thousands of SKUs;
• clear business ownership - responsibility not for accuracy, but for margin and ROI;
• production-first approach - models are immediately designed for production, automation and scaling;
• space for decision architecture - building a decision-layer, not separate models.

This role allows you to go from "I do ML" to "I manage how the business makes decisions based on ML".

Main tasks:

• Building ML direction: development and launch of ML models in production (demand forecasting, promo effect calculation, demand elasticity models, optimization assortment). Building MLOps processes, CI/CD for models.
• Responsibility for the business result of ML models: working together with all directorates of the company and transforming models into management and automated solutions.
• MLOps and production approach: building model training pipelines, CI/CD for ML, monitoring quality and drift. Quality monitoring for stable, scalable and reproducible models.
• Formation of the Data Scientists team, middle/senior mentoring and setting standards for features, validations and interpretability of models.
• Interaction with Data Engineering and BI: ensuring data quality, stable datasets and integration of model results into BI and operational systems.

We expect:

• 6+ years of experience in Data Science / Machine Learning
• Mandatory hands-on experience running ML models in production
• Proficient in Python and SQL; ML: sklearn, xgboost, lightgbm, deep learning (preferred); Time series forecasting; Recommender systems; MLOps: MLflow, Docker, Kubernetes, CI/CD
• Business-oriented thinking, ability to "sell" ML to business, leadership and mentoring, responsibility for the result
• Desirable experience in retail / FMCG / e-commerce

Wewe offer:

• Real impact of ML on business
• Large volumes of data and complex retail cases
• Strong data team and business support
• Competitive compensation and development