Задачи
•Develop real-time product and bundle recommendation engines, including dynamic slot placement optimized for conversion and margin.
•Build targeted promotion algorithms: personalized coupon and points issuance, behavioral triggers and dynamic bundling.
•Scale the multi-market customer segmentation engine (behavioral, demographic, psychographic and lookalike audiences, wallet push).
•Extend personalization models across web, app and in-store employee touchpoints.
•Build and operate ML pipelines, from feature preparation in BigQuery and Snowflake to deployment and monitoring.
•Design and evaluate A/B tests to prove the business impact of each model.
Требования
•Hands-on experience building ranking or recommender systems that run in production.
•Strong Python and SQL skills; experience with TensorFlow or PyTorch.
•Solid grounding in model evaluation and validation, both offline metrics and online results.
•Experience designing and analyzing A/B tests and experiments.
•MLOps experience: ML pipelines, model deployment, performance monitoring and CI/CD.
•Experience with cloud data warehouses, ideally BigQuery and/or Snowflake, and pipeline orchestration with Airflow.
•Experience with real-time or low-latency model serving.
•Experience with promotion, pricing or uplift modeling (e.g. coupon targeting, bundling).
•Customer segmentation and lookalike modeling across several markets.
•Infrastructure as code with Terraform.
•Experience on GCP ML tooling such as Vertex AI.
•Background in retail or e-commerce personalization.
•Fluent English for working in an international team.
Условия
•Medical insurance.
•In-house fitness trainer available remotely and 1-on-1 remote sessions with a Sports and Health Coach focused on nutrition counselling and tailored training plans.
•Starting from at least 21 vacation days (based on seniority), earning 1 extra day for each completed year of collaboration — up to 29 days — depending on tenure in the company and/or industry.
•Flexibility to work from both home and the office.
•Long-term learning programmes developing both technical and non-technical skills incrementally, with a Career Coach to discuss learning resources and platforms.
