active · Approximate location
Analyst II, Data Science (R-19664)
full timeChennai - India
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AT A GLANCE
TechnologyFull TimeEmployee: Full Time
Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted u
About the role
Shape the Future with Dun & Bradstreet
At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers.
Dun & Bradstreet Technology and Corporate Services India LLP are looking for candidates for the role of an Analyst to support the Data Science team. 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 the deliverables on a timely basis.
Responsibilities
- Work across a range of analytical solutions involving implementation, testing, validation, documentation, monitoring, investigations, and reporting.
- Extract, analyze, and validate large datasets from various data sources using tools such as Python, PySpark, SQL, and Hadoop to support analytics implementations and operational activities. Perform model scoring, result validation, impact analysis, score investigations, and periodic model monitoring to ensure accuracy and operational stability.
- Develop and support automation solutions, AI-driven tools, and operational efficiency initiatives to streamline analytical processes and reduce manual effort.
- Utilize custom-built frameworks and platforms for analytics implementations, validations, monitoring, reporting, and delivery activities.
- Support MLOps/LLMOps processes for deployment, monitoring, observability, validation, and governance of AI/ML solutions.
- Create and maintain technical documentation, implementation artifacts, operational procedures, and knowledge repositories.
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