Senior Data Scientist

OneTrust’s mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn’t slow teams down—it should accelerate what’s possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society.

The Challenge

OneTrust's platform supports complex, regulated workflows across privacy, consent, risk, and AI governance. Bringing measurement maturity to all these areas will help drive a new level of visibility into user experience, ultimately helping our customers achieve their goals.

We are hiring a Senior Quantitative UX Researcher to support our teams in data-driven decision-making: to define how experience is measured across the platform, to ensure the underlying data is valid and defensible, and to deliver analysis that informs roadmap decisions. This is the first quantitative research role on a newly expanded UX Research team, responsible for making our numbers defensible and then making them useful. You'll define how we measure the user experience of a complex enterprise platform, build the survey and behavioral measurement that answers real roadmap questions, and partner with designers and mixed methods researchers so that findings arrive with both the scale and the "why".

What you'll do

• Design and run quantitative studies: benchmarking, segmentation, driver analysis, prioritization research, unmoderated testing at scale, longitudinal tracking.
• Apply appropriate statistical methods and say plainly where the data cannot support the conclusion someone wants.
• Contribute quantitative evidence to our reports and planning inputs.
• Use storytelling methods to present data to product teams, UX, and R&D leadership.
• Contribute to and evolve the metric and continuous customer sentiment approach: sampling, instrument design, coding taxonomy, reporting cadence, and the reconciliation between raw data and BI reporting.
• Bring behavioral telemetry, survey data, and business signals (adoption, churn reasons, support volume) into one coherent view of experience health.
• Audit existing instrumentation and survey coding for validity, and