Data Scientist Credit Risk

As a Data Scientist specializing in Credit Risk & Machine Learning within the FINTECH industry, you will be joining a leading organization in Pune, India. Your role will involve developing and optimizing data-driven lending solutions, specifically focusing on credit risk analytics, money lending products, and fraud detection using machine learning techniques. Key Responsibilities: - Develop, enhance, and maintain credit risk and credit scoring models using advanced statistical and machine learning techniques. - Collaborate with third-party partners and data providers on credit scoring initiatives, model evaluation, and portfolio performance analysis. - Build predictive models for credit risk assessment, fraud detection, lending portfolio optimization, and other high-impact business use cases. - Analyze large and complex datasets to identify trends, opportunities, and risks that improve lending decisions. - Monitor, validate, and continuously improve model performance and effectiveness. - Work closely with Data Engineering and Software Engineering teams to develop scalable, production-ready solutions. - Create dashboards and reports that translate data insights into actionable recommendations for business stakeholders. - Stay updated on emerging trends, technologies, and regulatory developments within Data Science and Credit Risk. - Mentor junior Data Scientists and contribute to capability building within the team. - Support the Head of Data in driving the organization's data strategy. Qualifications Required: - Master's degree in Computer Science, Statistics, Mathematics, Economics, or a related quantitative discipline. - 2 - 3 years of experience in Data Science. - Prior FINTECH experience in credit scoring, digital/money lending products, and fraud detection and management. - Strong programming skills in Python and SQL (R is an added advantage). - Hands-on experience with model deployment, monitoring, CI/CD practices, databases, and scalable systems design. - Expertise in machine learning and statistical techniques such as Logistic Regression, Decision Trees, Random Forests, Gradient Boosting Machines, and Neural Networks. - Ability to translate business objectives into practical, data-driven solutions. - Excellent communication and stakeholder management skills. If you possess a strong FINTECH background with proficiency in credit scoring, lending, and fraud management, and are available for an immediate start or short notice period, we encourage you to apply with your updated CV and GitHub profile (if applicable). As a Data Scientist specializing in Credit Risk & Machine Learning within the FINTECH industry, you will be joining a leading organization in Pune, India. Your role will involve developing and optimizing data-driven lending solutions, specifically focusing on credit risk analytics, money lending products, and fraud detection using machine learning techniques. Key Responsibilities: - Develop, enhance, and maintain credit risk and credit scoring models using advanced statistical and machine learning techniques. - Collaborate with third-party partners and data providers on credit scoring initiatives, model evaluation, and portfolio performance analysis. - Build predictive models for credit risk assessment, fraud detection, lending portfolio optimization, and other high-impact business use cases. - Analyze large and complex datasets to identify trends, opportunities, and risks that improve lending decisions. - Monitor, validate, and continuously improve model performance and effectiveness. - Work closely with Data Engineering and Software Engineering teams to develop scalable, production-ready solutions. - Create dashboards and reports that translate data insights into actionable recommendations for business stakeholders. - Stay updated on emerging trends, technologies, and regulatory developments within Data Science and Credit Risk. - Mentor junior Data Scientists and contribute to capability building within the team. - Support the Head of Data in driving the organization's data strategy. Qualifications Required: - Master's degree in Computer Science, Statistics, Mathematics, Economics, or a related quantitative discipline. - 2 - 3 years of experience in Data Science. - Prior FINTECH experience in credit scoring, digital/money lending products, and fraud detection and management. - Strong programming skills in Python and SQL (R is an added advantage). - Hands-on experience with model deployment, monitoring, CI/CD practices, databases, and scalable systems design. - Expertise in machine learning and statistical techniques such as Logistic Regression, Decision Trees, Random Forests, Gradient Boosting Machines, and Neural Networks. - Ability to translate business objectives into practical, data-driven solutions. - Excellent communication and stakeholder management skills. If you possess a strong FINTECH background with proficiency in credit scoring, lending, and fraud manageme