Data Scientist, Analyst II

Dun & Bradstreet

. Develop B2B risk solutions, including standard and custom solutions for clients such as Fortune 500 companies .

Posted 9/18/2026full-timeChennai • IndiaJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing B2B risk solutions through advanced data science techniques, including Machine Learning and Natural Language Processing, while effectively communicating complex concepts to diverse stakeholders. Proven ability to manage multiple projects and collaborate with teams to deliver innovative risk analytics solutions.

Highest-signal resume keywords

Machine Learning ApplicationPython ProgrammingRisk Model DevelopmentData Science ExperienceSQL Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningNatural Language ProcessingRisk ModellingStatistical AnalysisData ManipulationXGBoostLightGBMRandom ForestLogistic RegressionNeural Networks

Soft Skills

Client Relationship ManagementEffective CommunicationAnalytical MindBusiness AcumenTeam Collaboration

Tools & Technologies

PythonPySparkSQL

Industry Keywords

B2B Risk SolutionsFinancial ServicesFraud DetectionComplianceData Science

Tech Stack

Tools & technologies

PySparkPythonSQL

About the role

Key responsibilities & impact

Develop B2B risk solutions, including standard and custom solutions for clients such as Fortune 500 companies
Work with internal and external Dun & Bradstreet clients and stakeholders
Participate in modelling engagements, including design, development, validation, calibration, documentation, approval, implementation, monitoring, and reporting
Apply LLMs and prompt engineering to large-scale structured and unstructured B2B datasets for credit risk, fraud detection, and compliance
Design, develop, and test risk signals to identify patterns in structured and unstructured data
Develop AI agents using Machine Learning and Natural Language Processing to detect real-time risk triggers and anomalies
Manage multiple assignments with challenging timelines
Work independently and collaborate effectively in a team environment
Partner with internal Dun & Bradstreet teams to develop new business solutions in risk analytics

Requirements

What you’ll need

Master’s degree or higher with concentration in a quantitative discipline such as Math/Stat, Economics, Computer Science, Finance, Operations Research, etc.
2–5 years of experience in Data Science
Experience in development of risk models is desirable
Application of Machine Learning Models using XGBoost, LightGBM, Random Forest, Logistic Regression, Decision Tree, Neural Networks, etc.
Strong programming skills using Python and PySpark to manipulate data and conduct statistical analysis
Strong SQL skills and experience working with large datasets
Ability to build and maintain relationships with clients
Ability to effectively communicate complex ideas to technical and non-technical audiences
Analytical mind and business acumen, especially in the Financial Services Industry
Working experience applying modern machine learning techniques
Good grasp of ML explainability methods and interest in cutting-edge ML algorithms