At CheQ, we’re turning the chaos of credit into a journey that’s clear, rewarding, and even a little fun. With ₹50,000 Cr+ in lifetime payments, a growing tribe of users (30%+ using more than two products), and $16M raised from marquee investors, we’re fast becoming India’s favorite way to go from credit -stressed to credit -smart.
Founded by ex -Flipkart leader Aditya Soni and backed by 3one4 Capital, Venture Highway, Ram Shriram, Lloyd Mathias and more, CheQ isn’t just another fintech, it’s a full -stack credit experience.
Here’s what makes us different:
• Credit, simplified â Track, pay, and optimise every credit card, loan, and bill in one smooth dashboard.
• AI that actually helps â Meet Wisor, India’s first AI -powered credit advisor giving real financial intelligence, not just data.
• More than payments â Rewards, instant loans, and an embedded wallet all stitched into one seamless journey.
We’re here to make managing money feel less like a chore and more like a win
What you’ll be doing
We aren't looking for someone to
build dashboards. We are looking for a scientist to build the "brain"
of our Fintech engine. As a Decision Scientist, your role is to decode complex
user behaviours and build scalable models that drive automated, real -time
decisions—from credit risk and fraud prevention to payment routing and product
stickiness.
Experience: Fresher
Role Type: Data
Science / Engineering
Key Responsibilities
- Causal Inference
& Behavioral Discovery:
Dig deep into high -dimensional datasets to move beyond
correlation. You will identify the true causal drivers of user retention and
lending propensity.
- Scalable Predictive
Modeling: Design and deploy real -time ML models for Lending Propensity and Fraud Detection.
- System Architecture
& Pipelines: You will build and maintain production -grade data pipelines
that serve features to models at scale with minimal latency.
- Strategic Decision
Influence: Distill complex algorithmic outcomes into
strategic recommendations for leadership.
Technical Skills
- Foundational
Science: Understanding of Statistical Modeling and Machine Learning. You
should be obsessed with understanding "The Why."
- Advanced Python: Knowledge of ML
ecosystem (scikit -learn, XGBoost/LightGBM, PyTorch/TensorFlow) and data processing frameworks.