Data Science
Core
Build and improve predictive models for product ranking, retrieval, user behavior prediction, and advertiser budget forecasting to power a retail media ad platform.
Role type
Senior IC data scientist (ranking & retrieval)
Builds
Production ranking and retrieval models, forecasting pipelines, and evaluation infrastructure for an ad engine.
Domain
Retail Media / AdTech
Deliverable
production ML models
Required skills
forecasting, ranking systems, retrieval systems, deep learning, Python, SQL, A/B testing, time-series analysis, regression
Preferred skills
retail media, auction/bidding systems, LLM-based retrieval, model distillation, approximate nearest neighbor search, learning-to-rank, multi-objective ranking
Technologies
PyTorch, FAISS, HNSW
Responsibilities
Develop and refine forecasting models for budget planning; build and improve retrieval models for product selection; develop and iterate on rankers combining relevance and business constraints; improve query and product representation; explore large datasets to identify trends and assess data quality; ship models into the ad engine and build training/evaluation pipelines; partner with Product and Engineering to integrate models into platform workflows.
Seniority
Senior, hands-on IC
