Lead User Experience Behavioral Scientist

UKG•Lowell, MA

33d•$145,600 - $209,300•Hybrid

About The Position

UKG is seeking a talented and passionate Lead User Experience Behavioral Scientist to drive the development of UKG AI product experiences. This role involves managing user behavior and sentiment analysis programs, and synthesizing data to provide deeper insights into the UKG experience. The position offers a leadership role within the UX Research team and the broader UX organization, reporting to the head of UX Research. This is a hybrid position requiring 3 days in the office.

Requirements

7+ years of experience in behavioral research, behavioral analytics, data science, or a related field, driving measurable business and user outcomes in digital product environments.
Passionate about hands-on behavioral research and analytics, including building research data infrastructure, instrumentation, reporting frameworks, and dashboards within fast-moving AI-first product organizations.
Demonstrated expertise conducting quantitative and behavioral research at scale using methods such as experimentation/A/B testing, predictive modeling, segmentation and cluster analysis, conjoint modeling, and behavioral telemetry analysis to understand adoption, trust, reliance (follow/verify/override), friction, and outcome patterns.
Experience delivering AI-assisted and conversational experiences, including ML or NLP familiarity, conversational analytics, and journey or intent modeling.
Strong proficiency with SQL and experience working with large-scale behavioral and product datasets to generate actionable insights, dashboards, visualizations, and executive-ready narratives.
Proficient with tools such as PowerBI (preferred), QuickSight, Looker, Tableau, Claude, and other AI-assisted analytics platforms.
Demonstrated ability to translate complex behavioral and product data into actionable recommendations and partner cross-functionally with Product, Product Operations, Data Science, Engineering, and UX teams to influence product strategy, experimentation, onboarding, and AI experience optimization.
Contributes to a collaborative, inclusive team culture through respect, humility, humor, and entrepreneurial spirit.
Demonstrates strong curiosity, reasoning and problem-solving skills.

Nice To Haves

Experience with enterprise SaaS, workforce technology, HR technology, or AI-enabled productivity platforms strongly preferred.

Responsibilities

Conduct quantitative and behavioral research using product telemetry, log data, and user sentiment to model adoption, reliance (follow/verify/override), intent, and outcome patterns that improve how UKG’s AI products deliver value to customers and end users.
Develop predictive and descriptive behavioral insights that identify drivers of adoption, friction, hesitation, and abandonment across user segments and roles.
Design and operationalize behavioral telemetry and measurement frameworks—instrumenting user interactions, workflows, and touchpoints to generate leading indicators of trust, reliance, and value realization.
Partner with Product, Data Science, and Product Operations to build scalable systems for behavioral data collection, experimentation, and continuous insight generation.
Lead causal and experimental research (e.g., A/B tests, quasi-experiments) to evaluate the impact of features, nudges, defaults, and automation levels on user behavior and business outcomes.
Translate behavioral data into actionable insights and decision frameworks that inform product strategy, including how to optimize time-to-value, confidence-to-action, and appropriate AI reliance.
Establish and evolve metrics that go beyond sentiment and usability to quantify behavioral outcomes—such as adoption, trust calibration, sustained usage, and intervention effectiveness.
Provide thought leadership on AI adoption and behavioral science, shaping product direction and influencing senior stakeholders with a clear, evidence-based perspective.
Elevate the team’s capabilities in quantitative, behavioral, and data science methods; mentor others in applying advanced analytics, experimentation, and behavioral frameworks to product development.
Raise the methodological bar within the User Research team and mentor other team members on quantitative methods and data science methods.