Data Scientist

Responsibilities:
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 and 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.
Requirements:
2-4 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 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), and 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, user profiling, and anomaly detection.
Communication: clear storytelling with data; can align stakeholders and drive decisions.
Tech stack:
MySQL
Python Programming
Machine Learning
Data Scientist
Natural Language Processing

Experience
2-6 yrs