Research Scientist Lead

National Payments Corporation of India (NPCI)

Mumbai, Hyderabad

On-site

INR 2,500,000 - 4,500,000

Full time

5 days ago

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Job summary

NPCI is seeking an experienced Data Scientist in Hyderabad to drive ML/AI initiatives across fraud detection, risk analytics, and behavioral intelligence. You will design, build, and deploy production-grade AI platforms handling billions of transactions with a focus on latency, reliability, and explainability.

You will work with domain experts, data platforms, and academia to develop cutting-edge solutions for India's largest digital payments ecosystem.

Qualifications

Design and implement ML solutions for fraud and risk analytics.
Develop scalable models for large-scale transaction data and anomaly detection.
Build feature engineering pipelines for real-time and batch processing.
Establish evaluation frameworks with business-aligned metrics.
Ensure explainability and governance in regulated financial environments.

Responsibilities

Design, develop, and deploy production ML systems at scale.
Collaborate with data platform and engineering teams to operationalize models.
Monitor model performance, drift, and governance in production.
Prototype novel AI approaches and publish findings with partners.

Skills

Supervised Learning

Unsupervised Learning

Time Series

Fraud Detection

Anomaly Detection

Model Evaluation

Explainability

Statistical Modeling

Big Data Analysis

Behavioral Analytics

Education

B.Tech / M.Tech / MSc / MCA in CS/AI/DS/Stats/Math

Tools

Python

SQL

PySpark

Scikit-Learn

TensorFlow

PyTorch

Keras

MLflow

Docker

Kubernetes

Job description

The Opportunity

You will be part of NPCI's Market Innovation & AI Engineering team, driving the development of next-generation Machine Learning and Deep Learning systems powering India's largest digital payments ecosystem.

This role focuses on solving large-scale real-world problems using advanced Machine Learning, Statistical Modeling, Deep Learning, Graph Analytics, and Distributed AI Systems. You will be responsible for designing, building, and scaling production-grade AI platforms that process billions of transactions while maintaining high standards of latency, reliability, explainability, and operational excellence.

The role offers a unique opportunity to work on:

Fraud Detection & Risk Modeling
AML & Financial Crime Analytics
Behavioral Intelligence Systems
Transaction Intelligence Platforms
Large Scale Anomaly Detection Systems
Graph-based Network Analytics
Real-Time Decisioning Systems
GPU Accelerated AI Workloads

You will collaborate closely with engineering teams, data platform teams, domain experts, and leading academic institutions to build cutting-edge AI solutions for large-scale financial ecosystems.

Job Details

Job Title: Data Scientist
Division: Market Innovation:
Experience: 6-10 Years
Education: B.Tech / M.Tech / MSc / MCA in Computer Science, AI, Data Science, Statistics, Mathematics or related fields
Employment Type: Full Time
Location: Hyderabad
Role Type: Permanent

Key Responsibilities

Machine Learning & Advanced Modeling

Design, develop, and deploy advanced Machine Learning solutions using supervised and unsupervised learning techniques.
Build and optimize predictive models for fraud detection, anomaly detection, transaction intelligence, risk scoring, and behavioral analytics.
Develop robust feature engineering frameworks for large-scale transactional datasets.
Design custom evaluation methodologies and business-aligned performance metrics.
Build explainable and interpretable AI systems for regulated environments.

Deep Learning Systems

Develop Deep Learning models utilizing Neural Networks, CNNs, RNNs, LSTMs, Autoencoders, Transformers, and Representation Learning techniques.
Optimize model architectures for production deployment and inference efficiency.
Design custom loss functions and optimization strategies for imbalanced datasets and complex business problems.

Production AI & MLOps

Design and implement scalable ML deployment pipelines.
Productionize Machine Learning models using containerized infrastructure.
Develop automated CI/CD workflows for model deployment and version management.
Implement model monitoring, drift detection, performance tracking, and rollback mechanisms.

AI Platform Engineering

Build high-throughput, low-latency inference platforms capable of supporting large transaction volumes.
Design feature engineering and feature serving architectures for real-time prediction use cases.
Collaborate with platform teams to optimize compute, storage, and data access layers.

Distributed AI Systems

Develop machine learning workflows for large-scale datasets utilizing distributed computing frameworks.
Build scalable data processing pipelines capable of handling billions of events and transactions.
Optimize training and inference workloads across multi-node environments.

Research & Innovation

Evaluate emerging techniques in Machine Learning and Deep Learning.
Contribute to innovative solutions, intellectual property creation, technical whitepapers, and research publications.
Collaborate with academic partners and industry experts on advanced AI initiatives.

Required Technical Skills

Core Machine Learning

Strong understanding of: