Note : If screened-in, you will be invited for initial rounds on 10th October 2026 (Saturday) in Bangalore.

Role Summary :

The Market Innovation team is responsible for building advanced AI-driven solutions across NPCI's digital payments ecosystem. The role involves leveraging traditional Machine Learning, Deep Learning, and Generative AI techniques to solve complex business problems such as fraud detection, AML risk modeling, anomaly detection, transaction intelligence, customer insights, and intelligent automation.

The incumbent will develop predictive and analytical models, RAG-powered applications, and agentic AI solutions using large-scale transactional, behavioral, and business datasets. The position requires expertise across the complete AI lifecycle including data exploration, data preparation, feature engineering, model development, evaluation, optimization, deployment, and monitoring.

The incumbent will work across the complete model lifecycle while collaborating with business, product, and engineering teams to deliver scalable, secure, production-grade, and impactful AI solutions.

Must Have Skills :

- Machine Learning : Supervised Learning, Unsupervised Learning, Classification, Regression, Clustering, Forecasting

- Statistical Techniques : Hypothesis Testing, Feature Selection, Multicollinearity, Model Evaluation, A/B Testing, Discriminant Analysis, Predictive Modeling

- Algorithms : Linear Regression, Logistic Regression, Random Forest, Gradient Boosting, XGBoost, LightGBM, Ensemble Methods

- Deep Learning : Neural Networks, CNN, Transformers, Transfer Learning

- Programming : Python, SQL

- Libraries : NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch

- Data Science : EDA, Feature Engineering, Model Development, Model Evaluation, Cross Validation, Hyperparameter Tuning, Imbalanced Data Handling

- NLP : Text Classification, Information Extraction, Entity Recognition, Language Modeling

- Generative AI : LLMs, Prompt Engineering, Fine-Tuning, Model Evaluation

- RAG : Embeddings, Vector Databases, Semantic Search, Retrieval Pipelines, Context Augmentation

- Agentic AI : AI Agents, Multi-Agent Workflows, Tool Calling, MCP (Model Context Protocol)

- Production AI : ML Pipelines, Model Monitoring, Batch & Real-time Inference

- Use Cases : Fraud Detection, AML Analytics, Anomaly Detection, Risk Analytics, Transaction Intelligence

Preferred Skills :

- Graph AI : Knowledge Graphs, Graph Neural Networks (GNNs), GCN, GAT, Network Analytics

- MLOps : ML Pipelines, Model Deployment, Model Monitoring, Monitoring Frameworks, CI/CD

- Cloud Platforms : AWS, Azure, GCP

- Data Engineering : Spark, Kafka, Distributed Data Processing

- Advanced AI : Agent Orchestration Frameworks, LLMOps, RAG Optimization

- Advanced Concepts : Federated Learning, Privacy-Preserving AI, Real-time Streaming Systems

- Domain : Payments, Fintech, Banking, Digital Transactions, Financial Risk Analytics