Senior Data Scientist

Overview

Build graph-native, statistical, AI/ML, and deep learning models for fraud, identity, and transaction risk. The role includes deploying production machine learning systems with real-time serving and observability.

What you'll do

• Build graph neural networks, embeddings, and graph algorithms.
• Detect fraud, collusion, and identity risk across banking and e-commerce networks.
• Design and deploy statistical, AI/ML, and deep learning models.
• Implement real-time model serving.
• Run experiments to improve model performance.
• Support light data pipeline work.
• Ship production-grade software with ML observability.

What you'll need

• 4 to 7 years in data science, AI, or ML engineering roles.
• BS, MS, or PhD in ML, computer science, mathematics, statistics, or a related field.
• Strong Python skills.
• Cloud experience with AWS, Databricks, or Azure.
• SQL, DBT, and Athena or BigQuery experience.
• Experience shipping production machine learning systems.
• Ability to work with ambiguous, unlabeled data autonomously.

Nice to have

• Experience in fintech fraud, risk, payments, or compliance.
• Prior graph-modeling experience.

Details

• Location: Bangalore.
• Competitive salary with potential equity.