Analyst II, Data Science

About Dun & Bradstreet

Dun & Bradstreet is a global leader in business decisioning data and analytics, helping companies worldwide to grow, manage risk, and innovate for over 180 years. Their diverse and collaborative team values creativity and bold ideas aimed at shaping the future.

Role Overview

The Analyst II, Data Science position within Dun & Bradstreet's Technology and Corporate Services India LLP supports the Data Science team focusing on Trade and Credit Risk Analytics. The candidate will collaborate with Indian and global analytics leaders to deliver solutions timely.

Key Responsibilities

• Develop B2B risk solutions, including standard and customized offerings for clients such as Fortune 500 companies.
• Engage with internal and external clients and stakeholders across all phases of modeling projects: design, development, validation, calibration, documentation, approval, implementation, monitoring, and reporting.
• Utilize large language models (LLMs) and prompt engineering to analyze extensive structured and unstructured B2B data (e.g., company news, annual reports) for credit risk, fraud detection, and compliance.
• Design, develop, and test innovative risk indicators to detect patterns from diverse data types.
• Create AI-powered autonomous agents leveraging machine learning and natural language processing to identify real-time risk triggers and anomalies, transitioning risk management towards predictive actionable insights.
• Manage multiple assignments effectively, meeting challenging deadlines.
• Work independently and as part of a team to drive results.
• Collaborate with internal teams to develop new risk analytics business solutions.

Candidate Profile and Skills

• Master's degree or higher in a quantitative field such as Mathematics, Statistics, Economics, Computer Science, Finance, or Operations Research with 2–5 years of data science experience.
• Experience in risk model development is advantageous.
• Proficient in machine learning algorithms including XGBoost, LightGBM, Random Forests, Logistic Regression, Decision Trees, and Neural Networks.
• Strong programming expertise in Python and PySpark for data manipulation and statistical analysis.
• Advanced SQL capability with experience handling large datasets.
• Excellent client relationship management skills.
• Effective communication skills to explain complex technical concepts to varied audiences.

Preferred Attributes

• Analytical thinking paired with business awareness, particularly within the financial services sector.
• Hands-on experience with state-of-the-art machine learning techniques.
• Continuous learning attitude towards new ML algorithms and interpretability methods.

Additional Information

The job title internally is Analyst II, Data Science. All official correspondence will come from an email domain ending with @dnb.com. The recruitment process may involve AI tools to assist in screening and assessment, however, final hiring decisions are made by human recruiters.