What Youll Do :

- 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 :

i. Enhance customer experiences and personalization

ii. Boost revenue via pricing/discount optimization

iii. Power user-to-user discovery and ranking (matchmaking at scale)

iv. Detect and block fraud/risk in real time

v. 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

What Were Looking For :

- 2- 4 years of DS/ML experience in consumer internet / B2C products, with 78 models shipped to production end-to-end.

- Proven, hands-on success in at least two (preferably 34) of the following :

i. Recommender systems (retrieval + ranking, NDCG/Recall, online lift; bandits a plus)

ii. Fraud/risk detection (severe class imbalance, PR-AUC)

iii. Pricing models (elasticity, demand curves, margin vs. win-rate trade-offs, guardrails/simulation)

iv. 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.