Ender Ricart

MIDS Student

ender_ricart@ischool.berkeley.edu

enderricart.medium.com

Focus

I am interested in improving the quality of data derived from humans through the combination of qualitative research with data science.

Specialization

Data Science

User Experience Design & Research

Biography

Dr. Ender Ricart

UX Researcher

PhD Anthropology, University of Chicago

enderricart@gmail.com

Medium

Academia to UX LLC

Youtube

ABOUT

I have experience across multiple companies (Amazon Alexa, LivePerson support chatbots, and Google Gemini) training NLP models on research derived data, building taxonomies inclusive of goldens, and working closely with engineering partners to quality test and fine tune.

EXPERIENCE

Google, Remote — Staff UX Researcher (Systems UXR)

2020 - present (4 years)

Teams: Google Cloud; Counter Abuse; Privacy, Safety & Security

Contributions & Impact:

As part of the counter-abuse team I led the user research and building of an NLP model leveraging Gemini that identifies and categorizes online abuses based on conversational user input. Impact included a reduction in enforcement turn around time, reducing abuse report “noise”, and improving report classification accuracy. Won Google Research Award for work.
With GCP Cloud Compute Engine, my research and product partnership was central to the concept ideation, product scoping, and successful launch for 6 net new offerings, including Batch computing, Flexible Use Discounts, Shared Reservations, Spot VMs, Task Queues, Dynamic Workload Scheduler, and a re-architecting of Machine Families structuring.
Thought leader and teacher, offering a bi-annual 8-part educational series on Qualitative Research Methods with over 100 enrollees per session. Introducing new research methods, including Hub-and-Spoke model and the Ethnographic Approach, as well as novel applications of UXR for changing technology, Systems UX Research.
Automated the identification and processing of end user abuse-reports through the application of NLP and Google AI technologies. Impact included improved accuracy in identifying online abuses and business savings.

LivePerson, Artificial Intelligence Research Team— Principal UX Researcher

2019 - 2020 (1 year)

Drove research on user perceptions of and expectations for message-based conversational AI. Variables included modality of communication, context of engagement, age/generation of user, and topic of conversation. Impacts included statistically significant improvement in customer satisfaction scores for chatbot conversations as well as an increase in volume of chats resolved by chatbot-only from 15% to 27% over a 3 month trial period.
Published series of Medium articles related to conversational design: Link 1, Link 2
Own patent for new ML training algorithm based on UXR insights into conversational structuring across turn-exchanges (patent: 11,522,818 · Issued Dec 6, 2022).
Designed and initiated a successful company wide UX project to redesign (UI) and re-architect (IA) LivePerson’s main product platform according to the user-centered Jobs-To-Be-Done framework. Methods included contextual inquiry and usability testing.

Amazon, Seattle — Sr. UX Researcher

2017 - 2019

Produced research insights that were used and adopted across Alexa and even more broadly in Amazon. Examples include: 1) The first research into customer privacy and security concerns related to the use of conversational AI as “creepy”, and 2) the creation of Alexa customer archetypes based on engagement behavior, emotional registers, and cognitive associations that were pairable with user account identifiers for targeted Alexa content.