Data Scientist - Machine Learning

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.

- Enhance customer experiences and personalisation.

- Boost revenue via pricing/discount optimisation.

- 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 to 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 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.