Data Science Analyst - Model Development

Dun & Bradstreet Technology and Corporate Services India LLP is looking for candidates to support the Data Science team in Trade and Credit Risk Analytics. The candidate needs to work closely with the team based in India and across a range of Analytics leaders who are located globally to fulfill delivery on a timely basis

Key Responsibilities:

• Work on development of B2B Risk solutions which includes Standard and custom solutions catering to various clients including fortune 500 companies
• Work with internal / external D&B clients and stakeholders; Participate in all aspects of a modelling engagement, including design, development, validation, calibration, documentation, approval, implementation, monitoring, and reporting
• Ability to applying LLMs, and prompt engineering to analyze large-scale, unstructured and structured B2B datasets (e.g., Company News, Corporate Annual Reports) for credit risk, fraud detection, and compliance.
• Design, develop and test new risk signals to effectively identify risk patterns from structured and Unstructured data
• Serve as a Subject Matter Expert on risk models within the Analytics team and with business users; consult with the business, as appropriate, on predictive modelling solutions
• Develop AI Agents for business risk monitoring, deploying autonomous agents. These agents utilize Machine Learning (ML) and Natural Language Processing (NLP) to detect risk triggers, anomalies in real-time, shifting risk management from reactive reporting to predictive, actionable insights
• Ability to manage multiple assignments, many of which with challenging timelines
• Ability to work independently, as well as collaborate effectively in a team environment
• Partner with internal D&B team to develop new business solutions in risk analytics

Key Skills:

What we are looking for:

• Master’s degree or higher with concentration in a quantitative discipline such as (Math/Stat, Economics, Computer Science, Finance, Operations Research, etc.) with 5 - 8 years of experience in Data Science.
• Proven experience on design and development of Risk models and frameworks
• Experience in design and development of risk models is desirable.
• Strong experience in Scorecard Development, application of Machine Learning Models using techniques such as Xgboost, Light GBM, Random Forest, Logistic Regression, Decision Tree, Neural Networks etc.,
• Strong programming skills with the ability conduct research utilizing Python and Pyspark to manipulate data and conduct statistical analysis
• Strong SQL skills and experience working with large datasets
• Strong client collaboration skills, including the ability to build and maintain relationships with clients
• Ability to effectively communicate complex ideas to both a technical and non-technical audience

Preferred Skills:

• Strong analytical mind and business acumen, especially in Financial Services Industry
• Proven working experience in applying modern machine learning techniques
• Passionate on stay abreast of cutting-edge ML algorithms, with good grasp of ML explain-ability methods
• Strong technical writing skills
• Familiarity with processing of unstructured data is a plus
• Experience in NLP / LLMs is mandatory