Fraud Data Scientist

Straive; Hyderabad, Gurugram District, Bengaluru; Hybrid; INR 1,800,000 - 3,000,000; Full time

Job summary

Straive invites applications for a Data Scientist / Senior Data Scientist focused on Fraud Risk. You will own end-to-end ML model development for payment fraud prevention, designing, building, and deploying high-throughput models and feature pipelines across card transactions, merchant activity, and account takeover scenarios.

The role requires 2 to 8 years of hands-on data science experience, with strong Python/SQL skills and a deep understanding of fraud patterns.

Qualifications

• 2 to 8 years of hands-on data science experience.
• Experience building ML models for fraud prevention.
• Hybrid work location across Bangalore, Hyderabad or Gurgaon.

Responsibilities

• ML Development: Build payment fraud models using XGBoost, LightGBM, and Isolation Forests.
• Feature Pipelines: Build velocity, temporal, and device features using Python and SQL.
• Decision Strategy: Optimize precision-recall trade-offs to balance fraud loss and friction.
• Model Lifecycle: Track production performance (PSI, drift) and manage retraining pipelines.
• Cross-Functional: Translate threat vectors into actionable rules and model signals.

Skills

Python

Pandas

NumPy

Scikit-learn

SQL

Fraud domain knowledge

Tools

XGBoost

LightGBM

Isolation Forests

Job description

Job Requirements

Data Scientist / Senior Data Scientist - Fraud Risk

Experience Range - 2 to 8 Years

Location - Bangalore / Hyderabad / Gurgaon (Hybrid)

Role Overview

We are looking for a Data Scientist with 2 to 8 years of experience to own end-to-end Machine Learning model development for payment fraud prevention. You will design, build, and deploy high-throughput fraud decisioning models and feature pipelines across card transactions, merchant activity, and account takeover scenarios.

Key Responsibilities

• ML Development: Build payment fraud models using XGBoost, LightGBM, and Isolation Forests.
• Feature Pipelines: Build velocity, temporal, and device features using Python and SQL.
• Decision Strategy: Optimize precision-recall trade-offs to balance fraud loss and friction.
• Model Lifecycle: Track production performance (PSI, drift) and manage retraining pipelines.
• Cross-Functional: Translate emerging threat vectors into actionable rules and model signals.

Technical Requirements

• Experience: 2 to 8 years of hands-on data science experience.

Core Tech Stack

• FRAUD Domain Knowledge: Understanding of FRAUD banking/payments, credit/debit card fraud patterns, transaction monitoring, account takeover (ATO), and velocity-based risk scoring etc.
• Python: Strong proficiency with pandas, numpy, scikit-learn.
• SQL: Good Hands on capabilities (complex joins, window functions, query optimization on large datasets).
• Machine Learning: Hands-on experience in building ML models.

About Company

Straive is a market leading Content and Data Technology company providing data services, subject matter expertise, & technology solutions to multiple domains. Data Analytics & Al Services, Data Al Powered Operations and Education & Learning form the core pillars of the company's long-term vision. The company is a specialized solutions provider to business information providers in finance, insurance, legal, real estate, life sciences and logistics. Straive continues to be the leading content services provider to research and education publishers.

Data Analytics & Al Services: Our Data Solutions business has become critical to our client's success. We use technology and Al with human experts-in loop to create data assets that our clients use to power their data products and their end customers' workflows. As our clients expect us to become their future-fit Analytics and Al partner, they look to us for help in building data analytics and Al enterprise capabilities for them.

With a client-base scoping 30 countries worldwide, Straive's multi-geographical resource pool is strategically located in eight countries - India, Philippines, USA, Nicaragua, Vietnam, United Kingdom, and the company headquarters in Singapore.

Website: https://www.straive.com/ Linkedin

Straive is an equal opportunity employer. We commit to celebrate diversity, equity and inclusion in the workplace.