Lead UX Researcher, SandboxAQ

• This role requires a seasoned researcher who can navigate ambiguity, work with emerging technologies, and is open to learning about new domains / industries
• +8 years of experience in User Experience Research, with a significant portion dedicated to complex software, enterprise solutions, or emerging technologies
• Proven ability to independently plan, execute, and synthesize qualitative and quantitative research, delivering impactful insights that drive product decisions
• Excellent communication, storytelling, and presentation skills, with the ability to clearly articulate research findings and their implications to diverse audiences, including technical and non-technical stakeholders
• Know how to use current, relevant AI tools and methods in your own work
• Experience working in fast-paced, agile environments and comfort with ambiguity and iteration
• Passion for understanding user needs and advocating for the user in product development
• Experience in AI / ML space (e.g., agents, LLMs)

Desirable

• The SandboxAQ AI Generation Engine (SAIGE) team's mission is to accelerate SandboxAQ’s mission of “Deep Impact at Scale," with a focus on quantitative AI and rapid prototyping
• Build next-generation AI capabilities that establish SandboxAQ as the global pacesetter in quantitative AI
• Identify, incubate, prototype, and launch new AI products for high-potential and longer-term use cases, proving (or disproving) their viability as high-impact, highly profitable business lines
• Support internal AI teams and help build new AI applications and infrastructures across SandboxAQ’s business units
• The SAIGE team operates on the following principles: Prototype with Velocity, Explore Boldly, Fail Smart, Learn Fast, Look Forward, and Share Knowledge
• This team's mission is to accelerate SandboxAQ’s mission of “Deep Impact at Scale," with a focus on quantitative AI and rapid prototyping
• We build next-generation AI capabilities, identify and incubate new AI products for high-potential use cases, and support internal AI teams
• As a Lead User Experience Researcher on this team, you will play a critical role in identifying customer needs and shaping the user experience of novel AI-driven products and prototypes
• You will be responsible for designing and executing research strategies that provide actionable insights to guide product development, ensuring we build impactful and user-centered solutions
• Lead and execute end-to-end user research projects, from defining research questions and methodologies to synthesizing findings and delivering impactful recommendations
• Champion a deep understanding of user needs, pain points, and behaviors related to quantitative AI and its applications in new domains (e.g., finance, agriculture, nuclear fusion)
• Partner closely with product managers, engineers, and business developers & strategists to identify research opportunities and embed user-centered thinking throughout the technology and product development lifecycle
• Develop and implement a variety of research methods, including but not limited to user interviews, usability testing, surveys, contextual inquiries, and diary studies, adapting approaches for rapid prototyping and iterative development cycles
• Create research-fidelity prototypes for directional concept testing and feedback
• Use and discover new AI tools to accelerate, broaden, and deepen research and discovery datapoints (quant & qual)
• Bring a strategic lens paired with tactical execution to help the team efficiently define, test, and iterate
• Translate complex research findings into clear, actionable insights and compelling narratives that inform product strategy, design decisions, and feature prioritization
• Contribute to the establishment of UXR best practices within this team and across SandboxAQ in partnership with the Head of Design & User Research
• Act as a key player in identifying and validating new high-potential and longer-term use cases for AI products
• Proactively scan the horizon for emerging UXR trends and methodologies relevant to AI and rapidly evolving tech landscapes
• Foster a culture of "Fail Smart, Learn Fast" by designing research that embraces experimentation and extracts valuable learnings from both successful and unsuccessful prototypes