Job responsibilities

• Manage end-to-end ML projects: problem definition → solution → testing → deployment → support.
• Work with data engineers to build datasets and define data requirements, and assess feasibility, risks, and constraints
• Work with data analysts to design and analyze A/B tests: metrics, splits, interpretation of results, and recommendations for deploying solutions.
• Develop and train models (classic ML + DL), including solutions for text and image embeddings; conduct offline evaluation and error analysis.
• Deploy the model and code to production (Python service), support releases and integrations.
• Be responsible for model quality post-launch: metrics, monitoring, drift/degradation, improvement plans, and support procedures.

Key qualifications

• 4+ years of experience as a Data Scientist (with specific experience in search / ranking / recomendations tasks).
• Experience managing end-to-end ML projects in production (from setup to support).
• Excellent understanding of classical ML: feature engineering, boosting, classification/regression, cross-validation, threshold selection, calibration.
• Experience with DL (PyTorch/TensorFlow): understanding of fine-tuning principles and model inference.
• Python (production-grade): readable code, tests for critical components, understanding of model/artifact packaging and service integration.
• Understanding of ML monitoring: quality metrics, drift, alerts, diagnostics, and support procedures.
• SQL proficiency sufficient for independent dataset building (joins, window functions).
• Experience with model interpretability and error analysis.
• MLflow / W&B / DVC or similar experiment tracking tools.
• Orchestration/pipelines (Airflow/Prefect/Dagster) and advanced data processing.
• English at the B2 (upper-intermediate) level.

We offer you

• Flexible schedules and opportunity to work remotely;
• Ambitious and supportive team who love what they do, appreciate each other, and grow together;
• Internal programs for adaptation and training, development of soft skills, and leadership abilities;
• Partial compensation for participating in external training and conferences;
• Corporate English school: Group and individual lessons, speaking clubs with colleagues from all over the world;
• Corporate prices on hotels and travel services;
• MyTime Day Off - an extra non-working day without loss of compensation.