AI/ML Data Scientist

Altimetrik; Bengaluru; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Altimetrik in Bengaluru seeks a seasoned Data Scientist/ML Engineer with 8+ years of experience, including 3+ years in production ML, preferably in payments/fintech with high-volume transactional data and real-time decisioning. You will build and deploy models, optimize for latency, and own monitoring/retraining strategies.

Proficiency in Python, SQL, cloud ML infrastructure (AWS/GCP/Azure), and tools like Spark and Airflow is essential.

Qualifications

• 8+ years of overall experience with 3+ years as Data Scientist/ML Engineer in payments/fintech contexts.
• Strong Python and SQL, and deployment/production ML experience including monitoring and retraining.
• Familiarity with classification, anomaly detection, and imbalanced-class problems.

Skills

Python

SQL

Production ML

Model Monitoring

Classification

Anomaly Detection

Imbalanced Data

Cloud Infra

SageMaker

Vertex AI

Databricks

Spark

Airflow

PCI DSS

Data Security

Communication

Tools

PyTorch

TensorFlow

SageMaker

Vertex AI

Databricks

Spark

Airflow

Job description

• 8+ years of overall experience, including at least 3+ years as a Data Scientist or ML Engineer, ideally in payments, fintech, banking, or another environment with high-volume transactional data and real-time decisioning.
• Strong 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).
• Strong communication skills - able to translate model outputs and trade-offs (precision/recall, false positive cost, latency) into business decisions for risk and product stakeholders.