Credit Risk Analyst – Lending Marketplace
Bengaluru
If you're seeing this form, the role is open.
About Oolka :
We are a Series A fintech start up looking to disrupt consumer fintech using AI
We are backed by one of the biggest global VCs and a marquee list of angel investors globally
Founded by Utkrishta Kumar (ex Chief Business Officer, Meesho)
About the role :
At Oolka, AI isn't a layer on top. It's the product. You will play a key part building our lending marketplace.
As a Credit Risk Analyst, you will own the data and decisioning behind that marketplace. You will sit at the intersection of risk, lender partnerships, AI product, Tech and Data Science, deciding every user gets the right loan
Our office is in Bangalore and we don't offer remote.
In addition to cash, we offer generous ESOPs, productivity reimbursements and health insurance to everyone.
What you will work on
Lending strategy - Design the logic that decides which lenders a user sees and in what order, balancing approval likelihood, offer quality and lender economics. Define eligibility and figure out invisible rejection signals for various lenders.
Scoring and ML models - Build user quality scores and approval-probability models from bureau, SMS and bank statement features, and put them into production decisions.
Lender MIS and performance. Reconcile lender reports with our own data, track approval, rejection and disbursal by lender, and turn that into actions on policy and lender mix.
Funnel and conversion. Measure conversion at every stage from intent to disbursal, across lenders and user segments. Diagnose where and why users drop off, and drive fixes with product and lender teams.
Who we are looking for
1 to 4 years as a Risk Analyst, Credit Risk Analyst or Business Analyst in consumer lending: an NBFC, bank, fintech lender or lending marketplace / DSA.
Tier-1 college preferred.
Strong hands-on SQL, Python for analysis and light automation.
Hands-on with credit bureau data (CIBIL / Experian / Equifax): tradelines, enquiries, scores, and how to build features from them.
Understanding of the unsecured lending funnel and credit mechanics: policy and BRE rules, pre-approved programs, KYC and disbursal, and what drives approval and rejection at a lender.
Ownership mindset: You can take a broad problem, define the metric, pull the data, and land a recommendation without waiting to be told each step.
Good to have
Built or maintained Risk scorecards, logistic or tree-based models, or user segmentation for credit decisions.
Experience working with SMS, transaction or bank statement data.
Prior experience working in fast-paced, tech-driven environments with a focus on financial services.