8+ years of overall experience, including at least 3+ years as a Data Scientist or ML Engineer, ideally in payments, fintech, banking, or another workplace with high-volume transactional data and real-time decisioning.
Solid proficiency in Python (pandas, scikit-learn, XGBoost/LightGBM, PyTorch or TensorFlow) and SQL.
Demonstrated experience building and deploying models into production (not just research/exploratory work), with attention to monitoring and retraining considerations.
Solid understanding of classification, anomaly detection, and imbalanced-class problems (fraud is a classic rare-event problem).
Experience with cloud data/ML infrastructure (AWS/GCP/Azure - e.g., SageMaker, Vertex AI, Databricks) and standard data engineering tools (Spark, Airflow, or similar).
Understanding of the regulatory and security constraints of financial services data (PCI DSS, data minimization, access controls).
Robust communication skills - able to translate model outputs and trade-offs (precision/recall, false positive cost, latency) into business decisions for risk and product stakeholders.

📌 Ai/ml Data Scientist Bengaluru
🏢 ALTIMETRIK
📍 Bengaluru