The Kuhoo Story: Where Dreams Meet Data Picture this: A brilliant engineering student from a middle-class family in Tier-2 India has the potential to revolutionize technology, but traditional lenders see only their father's modest income. This is the story that sparked Kuhoo Finance—a fintech revolution that believes in Aatmanirbharta (self-reliance) and transforms "what if" into "why not."
Today, we're not just another NBFC. We're dream architects, wielding AI and data science like modern-day magic wands to unlock the future earning potential hidden within every student. With our fresh RBI NBFC license, we're scaling from facilitating dreams to directly funding them—offering education loans up to ₹2 crore across engineering, management, medical programs, and cutting-edge upskilling initiatives.
Our Numbers Tell Stories:
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100,000+ student applications processed (each one a unique dream)
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₹375+ crore in loans facilitated (translating to countless transformed lives)
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15,000 borrowers who now call us their launchpad to success
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3 years of redefining how education financing works in India
Our DNA:
The Five Core Values That Drive Us
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Ownership: We don't just work here; we build the future here
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Passion for Excellence: Good enough is never good enough
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Impact: Every line of code, every decision shapes a student's tomorrow
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Curiosity: We question everything and innovate fearlessly.
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Fairness: At Kuhoo, fairness is the foundation of our decisions, ensuring equal opportunities and transparent growth for all.
At Kuhoo, we've created more than a workplace—we've built an ecosystem where innovation thrives, execution is an art form, and meritocracy isn't just a buzzword but our operating system. As we scale, our Data & Analytics team plays a central role in shaping product strategy, credit risk, and marketing effectiveness.
We are looking for an experienced Senior Data Scientist / Analyst to join our Data & Analytics team. This is a broad, high-ownership analytics role. You will run detailed credit risk analysis — which makes up the bulk of the work today — service day-to-day data requests, and build and own Tableau dashboards, while partnering closely with credit, product, and marketing teams to turn questions into decisions. You are expected to understand the business in depth and drive projects independently, end to end. As the team and data mature, you will mentor junior analysts and progressively take on more advanced modelling and machine learning as the company scales.
Credit Risk Analysis & Decisioning
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Own detailed credit risk analysis — portfolio cuts, delinquency and roll-rate trends, vintage and cohort performance, and the drivers of risk across the loan book.
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Work hands-on with CIBIL, Experian, and CRIF bureau data: understand the schema, assess data quality, and build predictive features and risk segments.
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Develop and refine credit decision rules and policy frameworks to support automated and assisted underwriting.
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Build and maintain credit scorecards and risk monitoring; track performance, watch for drift, and recommend recalibration as volumes grow.
Data Requests, Reporting & Dashboards
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Service ad-hoc and recurring data requests from credit, product, marketing, and leadership with accurate, well-documented SQL.
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Design, build, and own Tableau dashboards for operational and executive audiences — keeping them reliable, intuitive, and self-serve.
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Define metrics and single sources of truth, and safeguard data quality, consistency, and clear documentation across reports.
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Automate recurring reporting so the team spends less time pulling data and more time interpreting it.
Business, Product & Marketing Analytics
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Build a deep understanding of the business and use it to frame problems, scope analyses, and run projects independently from question to decision.
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Partner with product teams to define success metrics, instrument data collection, and analyse the impact of specific features.
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Design and analyse A/B and other experiments across marketing and product, and translate the results into clear recommendations.
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Build user segmentation and cohort analyses to support lifecycle marketing, acquisition efficiency, and product personalisation.
Leadership & Collaboration
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Mentor and guide junior data analysts and associates; review their queries and analysis and uphold analytical standards.
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Partner with engineering and data teams to source new data, improve pipelines, and embed analysis into day-to-day decisions and workflows.
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Communicate findings clearly — written memos, executive presentations, and data visualisations.
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Drive a culture of intellectual honesty: flag data limitations and uncertainty in conclusions proactively.
Machine Learning & Advanced Modelling (Future Scope)
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Today the role is analytics-led; as data volumes and the team grow, you will progressively take on more predictive modelling and machine learning.
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Apply techniques such as logistic regression, gradient boosting, clustering, and survival analysis to credit, marketing, and product problems where they add value.
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Help shape the team’s path from rules- and analysis-driven decisions toward more automated, model-driven decisioning over time.
Tools, Automation & Best Practices
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Use Python and SQL to automate repetitive data preparation, monitoring, and reporting tasks.
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Champion best practices for version control, reproducibility, and documentation across the team.
Core (Must Have)
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Python: Pandas, NumPy, Statsmodels, and Seaborn/Matplotlib for data wrangling, analysis, and visualisation (Scikit-learn / XGBoost a plus).
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SQL (advanced): complex queries, window functions, query optimisation on large datasets.
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Applied statistics: regression, hypothesis testing, experimental design, and segmentation for business and credit analysis.
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Credit bureau data: familiarity with CIBIL, Experian, or CRIF data structures and tradelines.
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Credit risk metrics and scorecard concepts: Gini, KS, PSI, IV, and basic model monitoring.
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BI / Visualisation: Tableau (or similar) — building and maintaining dashboards for operational and executive audiences.
Good to Have
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ML / model deployment: integrating models into production via REST APIs, Airflow pipelines, or rule engines.
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Advanced ML: gradient boosting, scikit-learn pipelines, and exposure to predictive modelling for credit or marketing.
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App analytics: Mixpanel, CleverTap, or Appsflyer for funnel analysis and event-level data.
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Cloud & big data: AWS / GCP, Spark, or equivalent for large-scale data processing.
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Version control and reproducibility: Git and reproducible pipeline practices (MLflow or similar a plus).
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4+ years of hands-on experience in data analytics / data science, preferably in fintech, NBFC, or a lending-focused startup.
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Degree from a Tier-1 institution (B.Tech / M.Tech in CS).
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Demonstrated ownership of end-to-end analyses or projects that drove measurable business outcomes.
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Strong grounding in credit risk analytics, with exposure to marketing and/or product analytics.
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Hands-on experience servicing data requests and building dashboards (Tableau or similar) for business stakeholders.
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Proven ability to operate in ambiguity — comfortable working without fully defined specs and iterating quickly.
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Strong communication skills: ability to translate technical findings for non-technical stakeholders.
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Analytical rigour — asks 'why' and 'so what' before jumping to analysis or modelling.
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Direct experience with student lending, education fintech, or consumer credit underwriting.
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Experience with alternative data sources: telecom, UPI, utility, or social data for credit thin-file populations.
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Exposure to RBI / NBFC regulatory and portfolio reporting requirements relevant to credit.
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Familiarity with fairness, explainability, and bias mitigation in credit models (SHAP, LIME, disparate impact).
Speed over Perfection Good answers fast beat perfect answers late.
Intellectual Honesty
Flag when data is insufficient or conclusions are uncertain.
Ownership
Follow a problem through to a decision, not just a deliverable.
Curiosity to Learn
Dive into new domains — credit, marketing, product — with equal enthusiasm.
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Competitive salary commensurate with experience and market benchmarks.
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Performance-linked variable pay tied to individual and company outcomes.
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ESOPs available, aligned with company growth milestones.
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Health insurance, flexible working, and learning & development budget.
Apply now and help us unlock education for every Indian student.
