Senior Credit Risk Data Science Analyst

Role Overview Dun & Bradstreet Technology and Corporate Services India LLP is seeking a Senior Credit Risk Data Science Analyst to strengthen its Trade and Credit Risk Analytics team. In this role, you will work closely with data science professionals across India and global analytics leaders to deliver high-quality risk solutions on time. You will be instrumental in building B2B risk frameworks, leveraging advanced AI and machine learning capabilities to serve Fortune 500 clients and more. Key Responsibilities - Design, develop, and test B2B risk solutions including standard and custom models for a wide range of clients including Fortune 500 companies - Participate in all stages of modelling engagements such as design, development, validation, calibration, documentation, approval, implementation, monitoring, and reporting - Apply Large Language Models and prompt engineering techniques to analyse structured and unstructured B2B datasets including company news and corporate annual reports for credit risk, fraud detection, and compliance purposes - Develop AI Agents for real-time business risk monitoring using Machine Learning and Natural Language Processing to detect risk triggers and anomalies - Identify risk patterns from both structured and unstructured data by designing new risk signals - Act as a Subject Matter Expert on risk models within the analytics team and advise business users on predictive modelling solutions - Manage multiple assignments simultaneously while meeting demanding timelines - Collaborate with internal D&B teams globally to build innovative business solutions in risk analytics Required Qualifications - Master's degree or higher in a quantitative discipline such as Mathematics, Statistics, Economics, Computer Science, Finance, or Operations Research - 5 to 8 years of hands-on experience in data science with a focus on risk model design and development - Strong proficiency in scorecard development and machine learning techniques including XGBoost, LightGBM, Random Forest, Logistic Regression, Decision Trees, and Neural Networks - Solid programming skills in Python and PySpark for data manipulation and statistical analysis - Strong SQL skills and experience managing large datasets - Mandatory experience in NLP and Large Language Models - Excellent communication skills to present complex concepts to both technical and non-technical stakeholders - Strong client collaboration and relationship management skills Why Join Us Dun & Bradstreet offers a collaborative, globally connected environment where you can work on cutting-edge analytics projects that shape credit risk decisions for some of the world's largest companies. This is a unique opportunity to drive innovation in AI-powered risk management at a truly global scale.

- Master's degree or higher in a quantitative field such as Math, Statistics, Economics, Computer Science, or Finance - 5 to 8 years of experience in data science with focus on risk modelling - Proven expertise in scorecard development and ML techniques including XGBoost, LightGBM, Random Forest, Logistic Regression, and Neural Networks - Strong programming skills in Python and PySpark - Proficiency in SQL and working with large datasets - Mandatory experience in NLP and Large Language Models - Experience in applying prompt engineering to structured and unstructured data - Strong technical writing and communication skills - Familiarity with AI Agent development for risk monitoring - Knowledge of ML explainability methods - Experience in financial services domain is a plus

- Opportunity to work with Fortune 500 clients - Collaboration with global analytics leaders - Exposure to cutting-edge AI and machine learning technologies - Full-time stable employment with a globally reputed organisation