Location
Hybrid in Tashkent, Uzbekistan, at 19 Shota Rustaveli Street.
Company
ACCESA supports employee wellbeing through health, fitness, work-life balance, and long-term learning programmes.
What you will do
•Develop real-time product and bundle recommendation engines with dynamic slot placement optimized for conversion and margin.
•Build targeted promotion algorithms for personalized coupons, points issuance, behavioral triggers, and dynamic bundling.
•Scale multi-market customer segmentation using behavioral, demographic, psychographic, and lookalike audiences.
•Extend personalization models across web, mobile app, and in-store employee touchpoints.
•Build and operate ML pipelines from feature preparation in BigQuery and Snowflake through deployment and monitoring.
•Design and evaluate A/B tests to demonstrate the business impact of each model.
Requirements
•Hands-on experience building ranking or recommender systems running in production.
•Strong Python and SQL skills, with experience using TensorFlow or PyTorch.
•Solid knowledge of model evaluation and validation, including offline metrics and online results.
•Experience designing and analyzing A/B tests and experiments.
•MLOps experience with 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, promotion, pricing, or uplift modeling, including coupon targeting or bundling.
•Experience with customer segmentation and lookalike modeling across several markets.
•Experience with Terraform and GCP ML tooling such as Vertex AI.
•Background in retail or e-commerce personalization.
•Fluent English for working in an international team.
Culture & Benefits
•Medical insurance and access to an in-house fitness trainer remotely.
•One-to-one remote sessions with a Sports and Health Coach, including nutrition counselling and tailored training plans.
•At least 21 vacation days based on seniority, increasing by one day for each completed year up to 29 days.
•Flexibility to work from home and the office.
•Long-term technical and non-technical learning programmes supported by a Career Coach.
