Data Scientist (Machine Learning) - Banking Domain

The Data Scientist role focuses on building propensity models and sizing market opportunities for VMO projects with banking clients. This hybrid position requires a blend of data science and engineering skills to create production-grade pipelines. The role is pivotal in driving sales strategy through data-driven outputs. Candidates should have a strong background in Python and SQL, along with proven experience in propensity modeling.
Job Responsibilities
1. Propensity Modeling & Ranking:
- Predict CTR and engagement probability
- Use models like XGBoost / LightGBM
- Optimize ranking using NDCG, MRR, Precision@K
2. Feature Engineering:
- Build features from user behavior, interaction signals, and context
- Handle sparse and noisy data
3 Cold Start Handling:
- Design strategies for new users and new offers
- Implement hybrid and fallback approaches
4. Bias Handling:
- Mitigate popularity and exposure bias
- Implement diversity and re-ranking strategies
5. Model Evaluation:
- Define and track CTR, conversion, NDCG, AUC
- Continuously improve engagement metrics
6. Scalability & Deployment:
- Build systems for millions of users
- Enable real-time or near real-time inference.