Senior Data Scientist in Strategic Finance managing simulation models for Relay's rapidly growing logistics network. Collaborating with finance teams to provide dynamic data - driven insights and improve decision - making.
About the role
- AI Engineer designing and operationalizing advanced AI driven solutions for data analytics at Dun & Bradstreet. Collaborating closely with data scientists and MLOps engineers to build production grade systems.
Responsibilities
- Build agentic workflows using LangChain/LangGraph and similar frameworks
- Develop autonomous agents for data validation, reporting, document processing, and domain workflows
- Deploy scalable, resilient agent pipelines with monitoring and evaluation
- Develop GenAI applications using models like GPT, Gemini, and LLaMA
- Implement RAG, vector search, prompt orchestration, and model evaluation
- Partner with data scientists to productionize POCs
- Build distributed data pipelines (Python, PySpark)
- Develop APIs, SDKs, and integration layers for AI-powered applications
- Optimize systems for performance and scalability across cloud/hybrid environments
- Contribute to CI/CD workflows for AI models—deployment, testing, monitoring
- Implement governance, guardrails, and reusable GenAI frameworks
- Work with analytics, product, and engineering teams to define and deliver AI solutions
- Participate in architecture reviews and iterative development cycles
- Support knowledge sharing and internal GenAI capability building
Requirements
- 8-12 years of experience in AI/ML engineering, data science, or software engineering, with at least 2 years focused on GenAI
- Strong programming expertise in Python, distributed computing using PySpark, and API development
- Hands on experience with LLM frameworks (LangChain, LangGraph, Transformers, OpenAI/Vertex/Bedrock SDKs)
- Experience developing AI agents, retrieval pipelines, tool calling structures, or autonomous task orchestration
- Solid understanding of GenAI concepts: prompting, embeddings, RAG, evaluation metrics, hallucination identification, model selection, fine tuning, context engineering
- Experience with cloud platforms (Azure/AWS/GCP), containerization (Docker), and CI/CD pipelines for ML/AI
- Strong problem solving, system design thinking, and ability to translate business needs into scalable AI solutions
- Excellent verbal, written communication and presentation skills
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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