Senior UX Researcher - Enterprise & AI‑Driven Workflows

Linda Werner & Associates

4d•Remote

About The Position

We are seeking an experienced Senior UX Researcher to support an enterprise product research team during a planned leave coverage period. This role focuses on qualitative research for internal financial and operational tools—including budgeting, planning, procurement, and spend‑management workflows—with the flexibility to support additional enterprise product areas as business needs evolve. The ideal candidate is a self‑directed researcher who can quickly ramp into unfamiliar domains, manage multiple stakeholder relationships independently, and incorporate AI‑assisted tools into their research workflow for analysis, synthesis, and operational efficiency.

Requirements

8+ years of UX research experience, with a strong focus on qualitative methods.
Demonstrated experience researching complex enterprise workflows (e.g., budgeting, forecasting, procurement, financial planning).
Proven ability to quickly ramp into new product areas and operate autonomously.
Strong stakeholder management skills, including experience partnering with product, engineering, and design teams.
Comfort with AI‑assisted research tools (e.g., large language models, automated analysis platforms).
Bachelor’s degree required.

Nice To Haves

Experience with enterprise business systems, financial planning tools, or supply‑chain‑related workflows.
Ability to pivot quickly between product areas and adapt to evolving business needs.
Familiarity with modern AI‑native research methodologies and tooling.

Responsibilities

Plan and conduct qualitative studies, including interviews, usability testing, and concept evaluations for enterprise financial and operational systems.
Investigate complex workflows such as budgeting, forecasting, procurement, and spend management.
Synthesize research findings into clear, actionable insights for product, engineering, design, and leadership stakeholders.
Manage research priorities across multiple product areas with minimal oversight.
Build strong relationships with cross‑functional partners and maintain consistent communication throughout the research lifecycle.
Present findings and recommendations in a concise, compelling format tailored to diverse audiences.
Use AI‑assisted tools to support research operations, including analysis, synthesis, coding, and summarization.
Integrate modern AI workflows into day‑to‑day research practices to accelerate insight generation and improve operational efficiency.
Independently manage timelines, expectations, and deliverables across concurrent research initiatives.
Adapt quickly to shifting priorities and new product domains.
Maintain high standards of quality, clarity, and rigor in all research outputs.