Senior Analyst - Data Science (R-19578)

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. For over 180 years, 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 is looking for candidates for the role of Senior 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

Key Responsibilities:

• Support and contribute to Generative AI initiatives across the organization.

• Develop and deploy GenAI applications using LLMs and AI frameworks.

• Leverage models such as GPT, Gemini, and LLaMA for AI-powered solutions.

• Build and manage multi-agent AI systems.

• Develop solutions using LangChain, LangGraph, FastAPI, Streamlit, Chainlit, and Transformers.

• Integrate AI capabilities into enterprise applications through APIs and cloud-native architectures.

• Design and implement RAG pipelines using vector databases such as FAISS, Qdrant, Weaviate, and ChromaDB.

• Collaborate with stakeholders to understand requirements and deliver AI-driven business solutions.

• Provide analysis, insights, and recommendations to support business needs.

• Stay current with emerging Generative AI technologies, tools, and best practices.

Key Requirements:

• Bachelor's degree in computer science, Engineering, Statistics, or a related technical field

• 6 - 8 years of experience in Data Analytics, Data Science, or Generative AI roles.

• Strong experience delivering data-driven and AI solutions in production environments.

• Proficiency in Python, PySpark, and SQL.

• Hands-on experience with data science libraries such as Pandas, NumPy, Scikit-learn, and Matplotlib.

• Experience with GenAI platforms and tools, including OpenAI, Anthropic, Google Vertex AI, FastAPI, Gradio, and Streamlit.

• Strong understanding of RAG (Retrieval-Augmented Generation) and Agentic AI architectures using LangChain and Lang Graph.

• Experience developing and deploying APIs using Fast API or similar frameworks.

• Knowledge of MLOps practices and machine learning deployment workflows is a plus.

• Strong analytical, problem-solving, communication, and stakeholder management skills.

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