We are looking for an experienced Data Scientist with strong expertise in credit risk, credit bureau analytics, and predictive modeling within the BFSI domain. The ideal candidate should have hands-on experience developing and productionizing statistical and machine learning models, translating credit and business problems into analytical solutions, and partnering with business, risk, policy, fraud, and product teams.

Responsibilities :

- Translate complex credit risk and business problems into end-to-end data science problems and scalable analytical solutions.
- Design, develop, validate, and deploy statistical and machine learning models for credit underwriting, risk segmentation, portfolio analytics, and related use cases.
- Leverage credit bureau data to generate insights and improve underwriting strategies, customer segmentation, risk assessment, and portfolio performance.
- Develop and optimize predictive models using techniques such as Logistic Regression, Linear Regression, Gradient Boosting, and other machine learning/deep learning approaches.
- Perform data exploration, feature engineering, model development, validation, performance monitoring, and model enhancement.
- Work with large and complex datasets using Python, R, Spark, and/or Databricks.
- Productionize machine learning models and collaborate with technology/MLOps teams on deployment, monitoring, retraining, and lifecycle management.
- Partner with Credit Policy, Credit Risk, Fraud Risk, Collections, Operations, Product, and Business teams to ensure models address key business objectives.
- Analyze model performance and portfolio trends and provide actionable recommendations to improve credit outcomes and business performance.
- Present model results, analytical findings, performance metrics, and strategic recommendations to senior management and business stakeholders.




- Identify new opportunities to apply advanced analytics and machine learning across the credit lifecycle.
- Mentor junior data scientists and analysts, provide technical guidance, and contribute to improving data science practices and capabilities.
- Ensure appropriate documentation, validation, governance, and monitoring of analytical models and solutions.

Requirements:

- 4 - 9 years of hands-on experience in Data Science, Data Analytics, or Machine Learning, with significant experience in credit risk and/or credit bureau analytics within BFSI.
- Strong hands-on experience in credit risk modeling, bureau analytics, underwriting, risk segmentation, or portfolio analytics.
- Strong mathematical and statistical foundation with practical experience in predictive modeling.
- Hands-on experience with Logistic Regression, Gradient Boosting/GBM, Linear Regression, and other machine learning techniques; exposure to deep learning is preferred.
- Advanced proficiency in Python and solid working knowledge of R, Spark, and/or Databricks.
- Experience working with large-scale customer, transactional, financial, and credit bureau datasets.
- Hands-on experience with model deployment, productionization, monitoring, and model lifecycle management.
- Strong understanding of model performance evaluation, feature engineering, validation, and statistical analysis.
- Experience collaborating with cross-functional teams across Credit, Risk, Fraud, Collections, Policy, Operations, and Product.
- Strong analytical reasoning, data interpretation, problem-solving, and structured thinking skills.
- Excellent communication and stakeholder management skills, with the ability to present complex analytical concepts to non-technical stakeholders.
- Experience mentoring team members or providing technical guidance is preferred.
- Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Data Science, Economics, Engineering, or another quantitative discipline.

📌 Data Scientist - Credit Risk/Predictive Modeling (India)
🏢 SKILLVENTORY
📍 India