About the Role :

We are seeking an experienced AI/ML Data Scientist to design, build, and deploy machine learning solutions for large-scale payment platforms. The ideal candidate will leverage advanced analytics, machine learning, and AI technologies to address business-critical challenges including fraud detection, risk scoring, authorization optimization, anomaly detection, and transaction monitoring.

Key Responsibilities :

Machine Learning & Model Development :

- Real-time fraud detection

- Card-not-present (CNP) risk scoring

- Authorization approval/decline optimization

- Merchant risk assessment

- Chargeback and dispute prediction

- AML and transaction anomaly detection

MLOps & Production Engineering :

- Deploy machine learning models in real-time and batch processing environments.

- Implement model monitoring, drift detection, performance tracking, and retraining strategies.

- Establish MLOps best practices including model versioning, CI/CD pipelines, reproducible training workflows, and A/B testing frameworks.

AI & Generative AI Applications :

- Utilize modern AI and LLM technologies (Claude, GPT, etc.) to enhance data science workflows.

- Develop AI-driven solutions for feature discovery, automated reporting, anomaly interpretation, and analyst productivity.

Required Skills :

Tech Stack : Python, Pandas, Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, SQL, AWS/Azure/GCP, Spark, Airflow.

- 10+ years of overall IT experience with at least 3+ years in Data Science or Machine Learning roles.

- Strong understanding of imbalanced datasets and fraud detection techniques.

- Master's or PhD in Computer Science, Statistics, Mathematics, Data Science, or related quantitative disciplines.