Role Overview

We are looking for a Data Scientist with strong experience in credit risk analytics, propensity modelling and bureau data

. The candidate will be responsible for developing and deploying data-driven models for credit products, customer segmentation, risk assessment and business decision-making.

Key Responsibilities

- Develop and validate credit risk, propensity and predictive models for various credit products.

- Work extensively with credit bureau data such as CIBIL/Experian/Equifax and other customer-level financial datasets.

- Perform data mining, feature engineering, statistical analysis and model development

.

- Build models to assess customer creditworthiness, probability of default, propensity to take a credit product and customer behaviour

.

- Work on customer segmentation, portfolio analytics and risk-based decisioning.

- Analyse large datasets and identify patterns, trends and actionable insights.

- Monitor model performance and support model validation, stability and optimisation

.

- Collaborate with Risk, Credit, Product and Business teams to translate analytical insights into business strategies.

- Prepare model documentation, performance reports and present findings to stakeholders.

Technical Skills

- Strong hands-on experience in

Python for data analysis and machine learning.





- Strong knowledge of

PySpark / Spark for processing large datasets.

- Experience with

SQL and large-scale data manipulation.

- Strong understanding of machine learning and statistical modelling techniques.

- Experience with classification, regression, propensity modelling and predictive analytics

.

- Knowledge of model performance metrics such as

AUC, ROC, KS, Gini, precision/recall

.

- Robust understanding of feature engineering, model validation and model monitoring

.

Domain Experience

- Mandatory experience in

Credit Risk / Lending / BFSI / Fintech

.

- Hands-on experience working with credit bureau data

.

- Exposure to credit products such as personal loans, consumer loans, credit cards, BNPL or other lending products

.

- Understanding of customer acquisition, credit underwriting and portfolio risk is preferred.

Education & Experience

- Bachelor's/Master's degree in

Computer Science, Statistics, Mathematics, Data Science, Economics or a related quantitative field

.

- Typically

3–7 years of relevant Data Science / Risk Analytics experience

, preferably within BFSI, lending or fintech.

- Strong business understanding along with hands-on modelling and programming expertise.

📌 Data Scientist- Risk/Propensity (3-6 years) - Immediate Joiners Preferred - BFSI/FinTech Only (Navi Mumbai)
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📍 Navi Mumbai