Data Scientist — PhonePe

About this Data Scientist role at PhonePe

PhonePe is hiring Data Scientists for its risk and fraud detection team in Bengaluru—a core role in India's fintech powerhouse. As a mid-level Data Scientist, you'll work on real-world problems protecting millions of transactions daily, building the machine learning systems that safeguard India's digital payments ecosystem.

What you'll do

• Build and deploy machine learning models for fraud detection and risk assessment across PhonePe's payment platform
• Develop statistical models to identify anomalies and patterns in transaction data at scale
• Work with Python to preprocess, analyze, and engineer features from fintech transaction datasets
• Collaborate with product and engineering teams to translate model insights into live risk management systems
• Monitor model performance in production and iterate on approaches to reduce false positives and fraud leakage

Who should apply

You need at least 3+ years of hands-on data science experience, ideally in fintech or payments. This is a mid-level role suited for Data Scientists who've shipped ML models in production and understand the intersection of machine learning and business impact. Prior exposure to fraud detection, risk modeling, or financial services is valuable—but core ML fundamentals matter most.

Salary & offer in context

PhonePe offers ₹30–55 LPA plus ESOPs for this role. For context, mid-level Data Scientists in India's private fintech sector typically earn ₹25–50 LPA; PhonePe's package sits at the competitive end of that range, reflecting the expertise and impact expected. At a high-growth fintech company like PhonePe, the equity upside can be meaningful over a 3–4 year horizon.

Path to apply

Apply directly through PhonePe's careers portal at phonepe.com/careers—no exam, no middleman. This is a straightforward online application for a permanent, full-time role based in Bengaluru. The application deadline is June 8, 2026, so move quickly if you're interested. Have your resume, portfolio of ML projects, and any GitHub links ready to showcase your modeling and coding skills.