Data Scientist - IPPB - Delhi

National Institute for Smart Government (NISG); New Delhi; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

National Institute for Smart Government (NISG) in New Delhi seeks a Data Scientist to analyze large transactional data from digital payments to identify fraud patterns and emerging risks.

You will develop and deploy ML models for fraud detection, money-mule identification, transaction risk scoring, and behavioural profiling, and collaborate with RBI-IH and cross‑functional teams to operationalize MuleHunter.AI and build real-time monitoring dashboards.

Qualifications

• 5+ years of post-qualification experience in ML/data science.
• At least 2 years in applied machine learning on transaction or large-scale structured data.
• Hands-on proficiency in Python/R, SQL, feature engineering, model validation and drift monitoring.

Responsibilities

• Analyze large data pertaining to digital payments and customer transactions to identify fraud patterns and emerging risks.
• Develop and deploy AI/ML models for fraud detection, money-mule identification, transaction risk scoring, and behavioural profiling; include back-testing.

Skills

Python

R

SQL

Feature engineering

Model validation

Drift monitoring

Education

B.Tech / Bachelors degree in Statistics/Mathematics/CS/Data Science/AI or related field

Tools

SAS

Job description

Designation - Data Scientist

Min. Educational Qualification

B.Tech / Bachelors degree in Statistics, Mathematics, Computer Science, Data Science, Artificial Intelligence, or a related field.

Min. Experience required

Minimum 5 years of post-qualification experience, with at least 2 years in applied machine learning on transaction, behavioural, or large-scale structured data

Hands-on proficiency in Python/R, SQL, feature engineering, model validation, and drift monitoring (SAS familiarity an advantage).

Location

Initially at Corporate Office, New Delhi (further as per requirement may be deployed at Bangalore, for RBI-IH MuleHunter.AI project)

Detailed Job Description

Analyze large data pertaining to digital payments and customer transaction (UPI, IMPS, AEPS, Mobile Banking, POS, ATM) to identify fraud patterns and emerging risks.

Develop and deploy AI/ML models for fraud detection, money-mule identification, transaction risk scoring, behavioral profiling and back-testing.

Work directly with Reserve Bank Innovation Hub (RBI-IH) on operationalizing MuleHunter.AI.

Collaborate with Fraud Risk, Compliance, Cybersecurity, and IT teams to translate data into real-time monitoring scenarios, reduce false positives, and build dashboards using SQL, Python/R.