Fraud Risk Analyst

What we do:

Money. It's always on our mind and often comes with a rollercoaster of emotions and complex jargon. That’s why at Jupiter, our mission is to improve your financial well-being by giving you full control over your money, helping you track, save, and invest with confidence.

We’re a financial services platform that uses technology to simplify money management. Whether it’s a savings account, payments, loans, credit cards, investments, or smart money tools it’s all on Jupiter. We break down banking jargon, offer spending insights, and give users modern features to make better financial decisions.

Our journey:

Jupiter was founded in 2019 by Jitendra Gupta (founder of Citrus Pay), who saw how broken personal finance felt compared to customer-first experiences like food or entertainment. We launched in 2021 with a 100,000+ waitlist. Today, 30 Lakh+ users trust us with their money.

We've built a team of creative thinkers and domain experts, driven by a shared vision of a transparent and inclusive financial ecosystem.

We’ve embraced cutting- edge technology with high ownership and deep customer obsession. Our team, spanning Mobile, Platform, Data, AI & ML — is building to scale products across the board. From AI to behavioural science, we’re creating world class banking experiences, and we’re looking for more builders to join us.

Who we're looking for:

We are looking for a data-first Fraud Risk Analyst with 2–4 years of hands-on experience to strengthen our fraud detection, prevention, and monitoring capabilities across multiple products. This role sits at the intersection of risk, analytics, operations, and product , and will directly influence fraud loss, customer experience, and platform trust.

This is not an operations role, you will spend a most part of your time working with data to identify patterns, test hypotheses, and influence product and policy decisions.

Roles and Responsibilities:

Fraud Detection & Monitoring

• Act as the first line of defense for fraud risk decisions within defined thresholds and playbooks.
• Monitor fraud risks across Lending, Credit Cards, UPI, Savings, Insurance, and Investment products
• Identify emerging fraud patterns, abuse vectors, and policy loopholes leveraging deep hands-on analysis of large datasets
• Design and maintain transaction monitoring rules, alerts, and thresholds
• Conduct detailed investigations into suspicious activities and high-risk accounts
• Translate insights into clear recommendations that influence product flows and policies

Analytics & Insights

• Own end-to-end fraud analysis from data extraction → insight → decision recommendation → post-impact measurement.
• Analyze large datasets to identify fraud trends, root causes, and early warning signals
• Build and track fraud KPIs such as fraud rate, false positives, customer impact, and recovery
• Support development and tuning of rule-based and ML-driven fraud models

Controls, Policy & Process

• Recommend improvements to fraud controls across onboarding, transactions, and lifecycle events
• Conduct root-cause analysis on fraud spikes and incidents
• Document fraud scenarios, SOPs, and escalation frameworks
• Partner with operations teams to improve case handling efficiency and quality
• Support audits, regulatory reviews, and internal risk assessments

Cross-Functional Collaboration

• Work closely with Product, Engineering, Data Science, Operations, and Compliance teams
• Provide fraud inputs during new product launches, feature changes, and experiments
• Translate fraud insights into clear business recommendations

What is needed for this role:

• 2–4 years of experience in fraud risk, transaction monitoring, or financial crime analytics
• Strong proficiency with Sql and Python
• Experience with real-time payments (UPI), card networks, or digital lending flows
• Exposure to ML-based fraud models or feature engineering
• Strong analytical rigor and problem-solving ability (IIT/NIT background or equivalent hands-on data depth preferred)
• Excellent communication, problem solving, and cross-functional collaboration skills.

Brownie Points for:

• Prior experience in scaling fraud systems in high-growth environments.
• Understanding of RBI guidelines, AML/KYC basics, and financial crime frameworks

Want to know more about us? Hop onto the links below:

• About us
• Our values
• Our Journey