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

Skills

Python, SQL, recommendation, recommender systems