Job Description

Who We Are

Escalent is an award-winning data analytics and advisory firm that helps clients understand human and market behaviors to navigate disruption. As catalysts of progress for more than 40 years, our strategies guide the world’s leading brands. We accelerate growth by creating a seamless flow between primary, secondary, syndicated, and internal business data, providing consulting and advisory services from insights through implementation. Based on a profound understanding of what drives human beings and markets, we identify actions that build brands, enhance customer experiences, inspire product innovation and boost business productivity. We listen, learn, question, discover, innovate, and deliver—for each other and our clients—to make the world work better for people.

The Role

This is a hybrid 6 month contract is at the intersection of behavioral science and applied AI. You don't need to be an engineer or write production code, but you do need to genuinely understand how AI agents work — their capabilities, limitations, and design patterns — well enough to translate behavioral science frameworks into agent logic, prompts, evaluation criteria, and workflows that a technical team can build and that non-experts across the firm can trust and use.

What You'll Do

• Lead testing and validation of AI outputs, using research data to refine prompts, improve decision logic, and ensure high-quality results.
• Translate behavioral science frameworks (e.g., dual-process theory, heuristics and biases, nudge design, choice architecture) into structured logic that AI agents can apply consistently
• Design and iterate on agent workflows, prompts, and decision rules that embed behavioral rigor into research design, survey/instrument development, qualitative analysis, and client deliverables
• Partner with engineering/product teams to spec agent requirements, define evaluation criteria for "did the agent apply this correctly," and QA agent outputs against behavioral science standards
• Build internal frameworks, playbooks, and training materials so consultants and researchers across the firm can use these agents appropriately (and know when not to trust them)
• Stay current on both behavioral science literature and the evolving capabilities of AI agents/LLMs, and identify new opportunities to scale behavioral expertise via AI
• Act as an internal translator between behavioral science rigor and technical implementation — flagging where an agent's approach oversimplifies or misapplies a behavioral concept
• Delivery Behavioral Science consulting to clients during development sprints when there isn't work for you to contribute to in the agent building workstream.

What You'll Bring

Required:

• Advanced degree (Master's or PhD) in behavioral science, psychology, cognitive science, behavioral economics, or a related field — or equivalent applied experience
• Strong grounding in behavioral science theory and its practical application to research and consulting
• Demonstrated interest in and working understanding of how AI agents/LLMs function — you can speak fluently about prompting, context, tool use, evaluation, and limitations, even if you've never written code
• Experience translating complex concepts into clear, structured frameworks that others (technical or not) can act on
• Comfort working in ambiguity — this function and the tools you're building don't fully exist yet

Preferred / Nice to Have

• Prior experience prompt-engineering, evaluating, or specifying requirements for AI/LLM-based tools (even informally)
• Experience in market research, consulting, or advisory settings
• Familiarity with agent frameworks or eval methodologies (conceptual understanding, not necessarily hands-on build experience)
• A portfolio of applied behavioral science work (published research, case studies, or client deliverables)