Senior Data Scientist

We are looking for a results-driven and technically strong Senior Data Scientist to join our Unsecured Lending Strategy team. This role will play a key part in developing data-driven pricing strategies and credit line decisions, powered by experimentation and machine learning. If you enjoy solving complex business problems with data and thrive in a fast-paced environment, we’d love to hear from you.

You’ll work at the intersection of pricing, risk, customer behavior, and machine learning, directly impacting customer conversion, unit economics, and portfolio quality.

Key Responsibilities

• Loan Pricing & Line Assignment:
• Develop pricing and credit line assignment strategies for unsecured lending products.
• Create dynamic frameworks that optimize offers for profitability, risk, and customer response.

Machine Learning Model Development:

• Build and deploy ML models for pricing, risk assessment, and customer response prediction.
• Apply techniques such as gradient boosting, logistic regression, decision trees, and model explainability (e.g., SHAP).
• Collaborate with engineering and product teams to productionize models and monitor performance.

A/B Experimentation:

• Design and lead A/B tests for pricing and offers to identify impact on customer acquisition and credit performance.
• Analyze experiment outcomes, provide recommendations, and iterate on strategies.

Price Sensitivity & Conversion Analysis:

• Conduct price sensitivity modeling to evaluate customer response across segments.
• Quantify how price changes affect both conversion and risk-adjusted returns.

Risk Correlation Analysis:

• Assess the impact of pricing and credit line strategies on risk metrics such as default rate, NPA, and early delinquency.
• Ensure pricing strategies are aligned with credit policy and portfolio risk appetite.

Cross-functional Collaboration:

• Work closely with risk, credit, product, and growth teams to align strategies and share insights.
• Present complex analytical results in a clear and business-relevant manner to stakeholders.

Qualifications

• 2–6 years of experience in data science, credit analytics, or machine learning in the financial services or fintech industry.
• Strong hands-on experience in unsecured lending, especially in pricing, line assignment, and risk strategy.
• Proficiency in Python and/or R, with strong SQL skills.
• Experience building and deploying machine learning models in production environments.
• Solid grasp of A/B testing, experiment design, and causal inference techniques.
• Strong foundation in statistics, predictive modeling, and data-driven decision-making.

Preferred Qualifications

• Experience with ML libraries such as XGBoost, LightGBM, scikit-learn, or TensorFlow.
• Exposure to credit risk modeling (PD, LGD, EAD) and profitability modeling (NPV, ROI).
• Familiarity with cloud platforms (AWS, GCP, or Azure) and model monitoring tools.
• Experience with dashboarding tools (e.g., Tableau, Power BI) for reporting and stakeholder communication.

Why Join Us?

• Direct impact on business strategy, customer experience, and financial outcomes.
• Work with a passionate team solving real-world problems in lending.
• Opportunity to develop advanced ML solutions in a data-rich and fast-paced environment.