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AI & Workforce Signals Analyst

Robert Half

NEW YORK CITY

Job at a glance

NEW YORK CITY
Location
Hybrid
Work arrangement
Robert Half
Employer

JOB REQUISITION AI & Workforce Signals Analyst LOCATION NEW YORK CITY ADDITIONAL LOCATION(S) JOB DESCRIPTION You Belong Here   The Protiviti Career provides   opportunity   to learn, inspire, and advance within a collaborative and inclusive culture. We hire curious individuals for whom learning is a passion. We lean into our mission:   We Care. We Collaborate. We Deliver. At every level, we champion leaders who   live   our values of   integrity, inclusion, innovation, and commitment to success .

Imagining our work as a journey, we believe integrity guides our way, inclusion moves us forward together, innovation creates new destinations, and our commitment to success empowers us to deliver on our vision to be the most trusted global consulting firm. Where We Need You   We are looking for an AI & Workforce Signals Analyst to join our People Analytics team. Protiviti works in a hybrid   environment   and this role requires that you work in-person in our office several times per week.

What You Can Expect   This role is designed for a technically strong, AI-forward individual who is passionate about applying artificial intelligence, NLP, and automation to people and workforce data at enterprise scale. You will work at the intersection of   people   data, advanced analytics, and AI engineering ,   building production-ready solutions that generate insights and signals across skills, roles, experiences, engagement, learning, and talent movement.

This role goes beyond traditional reporting to enable predictive, explainable, and scalable workforce intelligence. You will make an impact by embodying a key   component   of our mission “We Deliver.” In this role you will partner with HR, IT, and business stakeholders to build AI-powered tools that help leaders better understand and act on workforce signals ,   translating advanced models into insights people across the enterprise can trust and use.

What You Will Be Doing   Design and implement AI-based signal generation across   people   data, including skills inference, engagement signals, and talent movement patterns. Apply natural language processing (NLP) and Large Language Models (LLMs) to extract   aggregated   insights from HR data such   as anonymized   survey comments, performance feedback, project feedback, collaboration behaviors, and learning content.

Develop explainable AI outputs that help leaders understand not just what is happening in the workforce, but why. Build agentic AI workflows that automate and augment   people   analytics processes (e.g., skills validation, data quality checks, insight generation). Reduce manual analytics effort while   maintaining   transparency, accountability, and governance. Integrate AI capabilities with enterprise people systems (HRIS, skills platforms, learning systems, survey tools).

Design and   maintain   data architectures that securely combine LLM reasoning with   people   data. Partner with HR, IT, and stakeholders to ensure solutions align with enterprise privacy, security, and responsible AI standards. Deliver scalable, production-ready AI solutions that meet enterprise performance and quality standards. Continuously evaluate and update model performance, relevance, and trustworthiness.

As the People Analytics team partners across a global organization, you may occasionally   be required   to work outside typical business hours to accommodate meetings across multiple time zones. What Will Help You Be Successful   You care about applying technology to real human problems, thrive in a dynamic environment, embrace change with agility, strive for excellence, and champion Protiviti’s organizational culture   You   can   communicate technical concepts clearly and apply them to a business context   Strong   proficiency   in Python and experience building APIs or data pipelines   Hands-on experience with LLMs, NLP, and generative AI Experience working in cloud environments (Azure preferred)

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