Data Scientist, Specialist

Vanguard•Malvern, PA

26d•Hybrid

About The Position

This role focuses on solving business problems using Artificial Intelligence, specifically Agentic AI, Large Language Models (LLMs), and Natural Language Processing (NLP). The Data Scientist will partner with business stakeholders to identify and prioritize problems addressable by these technologies, translating business needs into clear AI use cases, success metrics, and delivery plans. A key aspect of the role is focusing on business outcomes rather than solely on model performance. The position involves architecting and developing agentic AI systems capable of reasoning, planning, and taking actions across various tools, workflows, and data sources, including designing multi-agent and tool-augmented LLM solutions for complex, multi-step processes. Ensuring the reliability, explainability, and governance of these solutions for enterprise use is crucial. Collaboration with engineering teams for scalable, secure, and performant deployment of AI solutions is expected, along with implementing evaluation, monitoring, and guardrails for LLM and agentic systems, addressing bias, drift, and failure modes. The role also requires aligning solutions with enterprise risk management, compliance, and responsible AI standards. The Data Scientist will act as a trusted AI advisor, educating teams on the value and limitations of Agentic AI and LLMs, contributing to AI best practices, reusable patterns, and strategic direction, and mentoring peers on applied AI and business-driven problem-solving.

Requirements

Agentic AI: Experience designing AI agents that reason, plan, and act across systems.
Large Language Models (LLMs): Hands‑on experience building enterprise LLM applications (e.g., RAG, tool use, orchestration, evaluation).
Natural Language Processing (NLP): Strong experience working with unstructured text and language‑driven workflows.
MS or PhD in Computer Science, Machine Learning, Data Science, or a related quantitative field.
3+ years delivering AI/ML solutions in production environments.
5+ years of hands‑on Python experience; experience with distributed data processing is a plus.
Strong ability to solve business problems using AI, not just build models.
Excellent communication skills, with the ability to explain complex concepts to both technical and non‑technical audiences.
Experience working in cross‑functional, enterprise environments.

Nice To Haves

Experience with distributed data processing is a plus.

Responsibilities

Solve Business Problems with AI
Partner with business stakeholders to identify, frame, and prioritize high‑value problems that can be addressed using Agentic AI, LLMs, and NLP.
Translate business needs into clear AI use cases, success metrics, and delivery plans.
Focus on business outcomes, not just model performance.
Design & Build Agentic AI Solutions
Architect and develop agentic AI systems that can reason, plan, and take actions across tools, workflows, and data sources.
Design multi‑agent and tool‑augmented LLM solutions to automate complex, multi‑step processes.
Ensure solutions are reliable, explainable, and governed for enterprise use.
Scalable & Responsible AI
Collaborate with engineering teams to deploy AI solutions with scalability, security, and performance in mind.
Implement evaluation, monitoring, and guardrails for LLM and agentic systems, including bias, drift, and failure modes.
Align solutions with enterprise risk management, compliance, and responsible AI standards.
Thought Leadership & Collaboration
Act as a trusted AI advisor, helping teams understand where Agentic AI and LLMs add value—and where they do not.
Contribute to AI best practices, reusable patterns, and strategic direction.
Mentor peers and teammates on applied AI and business‑driven problem solving.