Posted:1 week ago|
Platform:
On-site
Full Time
-Partner with Product to spot high-leverage ML opportunities tied to business
metrics.
-Wrangle large structured and unstructured datasets; build reliable features and
data contracts.
-Build and ship models to:
-Enhance customer experiences and personalization
-Boost revenue via pricing/discount optimization
-Power user-to-user discovery and ranking (matchmaking at scale)
-Detect and block fraud/risk in real time
-Score conversion/churn/acceptance propensity for targeted actions
-Collaborate 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 KPIs
-2–6 years of DS/ML experience in consumer internet / B2C products, with 7–8
models 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 with
warehouses/dashboards (Redshift/BigQuery, Looker/Tableau).
-ML breadth: recommender systems, NLP or user profiling, anomaly detection.
-Communication: clear storytelling with data; can align stakeholders and drive
decisions.
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