Stashfin - Data Scientist/Lead - Credit Risk Modeling

Stashfin; Gurugram District; On-site; INR 3,500,000 - 7,500,000; Full time

Job summary

Stashfin seeks a Lead Data Science & Growth Analytics to drive data-led growth, credit modelling, and customer lifecycle optimization. You will bridge risk, product, and growth, leveraging advanced analytics, ML, and LLMs to scale acquisition, improve conversion, and optimize portfolio profitability.

The role involves leading risk and growth analytics, building sophisticated models, and deploying scalable pipelines with a focus on improving disbursement performance and portfolio metrics across

Qualifications

• Strong Python/SQL/PySpark expertise.
• ML models experience (XGBoost, LightGBM).
• Credit risk modelling and scorecards experience.
• Growth analytics understanding (CAC, LTV, funnel metrics).
• Exposure to LLMs/NLP use cases.
• Proficiency with data viz tools (Power BI/Tableau).

Responsibilities

• Lead development of acquisition scorecards, behavioral models, and risk segmentation frameworks.
• Build and refine PD, LGD, and credit cost models.
• Optimize approval rates vs GCL in partnership with Risk teams.
• Drive champion-challenger and model recalibration strategies.
• Build propensity, intent, and LTV models across products.
• Drive CAC vs LTV analysis and marketing ROI improvements.
• Design NBA frameworks for personalization.
• Analyze end-to-end journey and identify conversion bottlenecks.
• Drive A/B testing for pricing, UX, and credit strategies.

Skills

Python

SQL

PySpark

ML models

credit risk modelling

growth analytics

LLMs/NLP

Power BI

Tableau

Education

Bachelor's/Master's in a quantitative field

Tools

Power BI

Tableau

Job description

Role Summary

We are looking for a Lead Data Science & Growth Analytics to drive data-led growth, credit modelling, and customer lifecycle optimization. The role will bridge risk, product, and growth, leveraging advanced analytics, ML, and LLMs to scale acquisition, improve conversion, and optimize portfolio profitability.

Key Responsibilities

• Credit & Risk Modelling :
• Lead development of acquisition scorecards, behavioral models, and risk segmentation frameworks
• Build and refine PD, LGD, and credit cost models
• Optimize approval rates vs GCL in partnership with Risk teams
• Drive champion-challenger and model recalibration strategies
• Growth & Customer Analytics :
• Build propensity, intent, and LTV models across products
• Drive customer acquisition, funnel optimization, and cross-sell strategies
• Analyze CAC vs LTV and improve marketing ROI
• Design Next Best Action (NBA) frameworks for personalization
• Product & Funnel Optimization :
• Analyze end-to-end journey (acquisition KYC approval disbursement retention)
• Identify and fix conversion bottlenecks
• Drive A/B testing for pricing, UX, and credit strategies
• Improve repeat usage and engagement across lending & payments products
• Advanced Analytics & AI/ML :
• Apply ML techniques (XGBoost, LightGBM, etc.) for risk and growth use cases
• Leverage LLMs/NLP for customer insights, document parsing, and automation
• Build feature engineering pipelines using bureau, banking, and behavioral data
• Explore alternate data for underwriting and growth
• Data Engineering & Deployment :
• Work with large datasets using PySpark / distributed systems
• Build scalable pipelines and deploy models (batch + real-time)
• Monitor model performance, drift, and stability
• Collaborate with Tech teams on MLOps and production systems
• Stakeholder & Team Leadership :
• Work closely with Risk, Product, Marketing, and Business teams
• Translate business problems into analytical solutions
• Lead and mentor a team of data scientists/analysts
• Drive data-driven decision-making across the organization

Required Skills

• Strong expertise in Python, SQL, PySpark
• Hands-on experience in ML models (XGBoost, LightGBM, etc.)
• Experience in credit risk modelling (scorecards, PD models)
• Strong understanding of growth analytics (CAC, LTV, funnel metrics)
• Exposure to LLMs/NLP use cases
• Experience with data visualization tools (Power BI/Tableau)

Preferred Qualifications

• Experience in Fintech / NBFC / Banking (Retail Lending)
• Exposure to bureau and alternate data (banking, app behavior, etc.)
• Experience with end-to-end model lifecycle (build ? deploy ? monitor)
• Strong business acumen and problem-solving skills

Key KPIs

• Disbursement / AUM growth
• Approval rate optimization
• GCL / Credit cost
• CAC vs LTV improvement
• Funnel conversion rates
• Cross-sell and retention metrics

Why Join Us

• Work on high-impact problems in digital lending and fintech
• Opportunity to drive end-to-end data strategy
• Fast-paced, ownership-driven environment
• Exposure to cutting-edge AI/ML and LLM applications

(ref:hirist.tech)