AI Scientist, Specialist

Responsibilities

• Own end-to-end design, development, and execution of complex predictive modeling initiatives, from problem formulation through validation, deployment readiness, and ongoing risk assessment.
• Lead the design, development, evaluation, and deployment of agentic AI solutions that orchestrate large language models, enterprise tools, and data sources to solve complex business problems.
• Evaluate emerging AI capabilities-including fine-tuning, prompt engineering, retrieval-augmented generation, and multi-agent architectures-and assess their relevance to Vanguard Workplace Solutions priorities.
• Lead deep-dive diagnostic, predictive, and prescriptive analytics to support data-driven decision-making, including alternative model approaches that advance future capabilities.
• Partner with senior leaders and business stakeholders to understand processes, shape hypotheses, clarify requirements, and translate business needs into actionable analytical approaches.
• Guide research design, model evaluation, validation, monitoring, and responsible-use practices, providing expert judgment on model performance, stability, governance, and appropriate application.
• Build reusable tools, frameworks, and shared resources that improve modeling efficiency, consistency, scalability, and quality across the analytics and AI community.
• Prepare and deliver clear, insightful presentations with recommended actions, communicating complex analytical findings and business implications to leadership audiences.
• Mentor and develop junior AI scientists and analysts through technical guidance, coaching, and knowledge sharing.
• Participate in special projects and perform other duties as assigned.

• Hands-on experience building LLM-powered applications, such as retrieval-augmented generation pipelines, prompt engineering workflows, fine-tuning approaches, or agentic frameworks including LangChain, LangGraph, or Google ADK.
• Related work experience in data science, AI, machine learning, or analytical roles, with strong experience applying statistical and machine learning methods to business problems.
• Experience with large language models, generative AI, knowledge graphs, and modern AI evaluation practices.
• Proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Experience with cloud platforms, such as AWS, and associated AI services, data platforms, and deployment tools.
• Strong stakeholder management, communication, storytelling, and collaboration skills, with the ability to influence technical and nontechnical audiences.