What You’ll Do
- Partner with Product to spot high-leverage ML opportunities tied to business
metrics.
Wrangle large structured and unstructured datasets; build reliable features anddata contracts.
Build and ship models to :Enhance customer experiences and personalizationBoost revenue via pricing / discount optimizationPower user-to-user discovery and ranking (matchmaking at scale)Detect and block fraud / risk in real timeScore conversion / churn / acceptance propensity for targeted actionsCollaborate with Engineering to productionize via APIs / CI / CD / Docker on AWS.Design and run A / B tests with guardrails.Build monitoring for model / data drift and business KPIsWhat We’re Looking For
2–6 years of DS / ML experience in consumer internet / B2C products, with 7–8models shipped to production end-to-end.
Proven, hands-on success in at least two (preferably 3–4) of the following :Recommender systems (retrieval + ranking, NDCG / Recall, online lift;bandits a plus)
Fraud / risk detection (severe class imbalance, PR-AUC)Pricing models (elasticity, demand curves, margin vs. win-rate trade-offs,guardrails / simulation)
Propensity models (payment / churn)Programming : strong Python and SQL; solid git, Docker, CI / CD.Cloud and data : experience with AWS or GCP; familiarity withwarehouses / dashboards (Redshift / BigQuery, Looker / Tableau).
ML breadth : recommender systems, NLP or user profiling, anomaly detection.Communication : clear storytelling with data; can align stakeholders and drivedecisions.