NinjaTrader aims to bridge the gap between complex trading workflows and intuitive product design by researching user needs, validating solutions, and optimizing the trading experience for their Futures Trading platform.
Requirements
- 5+ years of UX research experience in complex environments (fintech, trading, enterprise software, or similar domains)
- Expertise in a broad range of research methods, knowing when and how to apply each based on the research objective
- Experience conducting usability studies and optimizing workflows for high-stakes decision-making environments
- Ability to synthesize qualitative and quantitative insights to tell a clear and compelling user story
- Proficiency in UX research tools and behavioral analytics
- Experience with futures trading platforms or other financial markets
- Background in behavioral economics or cognitive psychology
Responsibilities
- Strategically select and apply research methods based on project needs
- Generative research to explore trader behaviors, workflows, and pain points
- Concept validation to refine ideas before development
- Evaluative research to assess the effectiveness of design solutions
- Behavioral and quantitative research to track user patterns and validate findings at scale
- Conduct deep research into trader psychology, decision-making under pressure, and automation workflows, ensuring the platform supports both expert and new-to-futures traders
- Collaborate with designers, product managers, and engineers to translate insights into user-centered solutions
Other
- Develop personas and journey maps to align stakeholders on trader goals and pain points
- Advocate for research-backed decision-making, ensuring UX is grounded in user needs rather than assumptions
- Present findings in compelling ways through reports, workshops, and data-driven storytelling
- Partner with market researchers and data analysts to triangulate user insights with behavioral data and market trends
- Establish and refine research frameworks, processes, and best practices to scale research impact across teams
