Senior Data Scientist

OneTrust•Atlanta, GA

16h•$116,475 - $174,713•Hybrid

About The Position

OneTrust is seeking a Senior Quantitative UX Researcher to support its teams in data-driven decision-making. The role involves defining how user experience is measured across the platform, ensuring the underlying data is valid and defensible, and delivering analysis that informs roadmap decisions. This is the first quantitative research role on a newly expanded UX Research team, responsible for making data both defensible and useful. The individual will define how to measure the user experience of a complex enterprise platform, build survey and behavioral measurements to answer roadmap questions, and partner with designers and mixed methods researchers to provide findings with both scale and context.

Requirements

6+ years in quantitative or mixed-methods UX research, market research, or product analytics, including work on complex B2B or enterprise software.
Deep survey methodology: sampling and its limits, questionnaire and scale construction, non-response and self-selection bias, longitudinal design.
Practical statistical fluency: significance testing, regression, segmentation and clustering, factor analysis, and the judgment to choose the simplest method that answers the question.
Working proficiency in SQL plus R or Python for analysis.
Hands-on experience with product analytics platforms (Pendo, Amplitude, Mixpanel, Heap, or similar), including defining and auditing instrumentation.
Experience with BI and warehouse environments (Power BI, Tableau, or Looker; Snowflake or equivalent).
A track record of defined metrics that were adopted and used in decisions.
Ability to state limitations clearly and hold a position under challenge.

Nice To Haves

Formal UX benchmarking experience (UX-Lite, SUS, SUPR-Q, task-based benchmarking).
Experimentation in enterprise contexts, where traffic is low and assignment is rarely random.
Familiarity with privacy, GRC, security, or another regulated, workflow-heavy domain.
Experience partnering with Engineering or QE on instrumentation standards.
Graduate training in a quantitative social science, HCI, statistics, or a related field.

Responsibilities

Design and run quantitative studies: benchmarking, segmentation, driver analysis, prioritization research, unmoderated testing at scale, longitudinal tracking.
Apply appropriate statistical methods and clearly state when data cannot support a desired conclusion.
Contribute quantitative evidence to 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.
Integrate behavioral telemetry, survey data, and business signals (adoption, churn reasons, support volume) into a coherent view of experience health.
Audit existing instrumentation and survey coding for validity, framing findings as evidence-backed rather than initiatives.
Diagnose the difference between real behavior change and measurement artifacts, and build checks to prevent future issues.
Coach teams on their use of quantitative data, as research efforts are shared between dedicated researchers and designers.
Review others' quantitative work against a consistent standard.