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 rigour 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
