Data Science Accelerator
A Data Scientist needs data in order to do their job. However, at present, it can be a rather complex process for them to get hold of Thomson Reuters data. This is why I was set out to validate the problem space with Data Scientists and created the concept of Data Science Accelerator.
Data Science Accelerator aims to make Thomson Reuters competitive in data science space that is rapidly growing and evolving. To achieve this, I designed methodology for customer engagement, interviewed Data Scientists around the globe and sketched and tested the concept.
ROLE: UX Researcher & Designer
METHODS: Workshops, User Interviews, Personas Prototyping & User Testing
TOOLS: Sketch & Invision
Shaping future work
My customer engagement methodology handover included:
Guidelines for approaching and recruiting customers
Interview guidelines for customer engagement
Presentation guideline for communicating the findings
Plan for further customer engagement
This project was a one of a kind example of broad and systematic customer engagement at Thomson Reuters. My work with customer engagement received extremely positive feedback across the organisation. I documented my process so that in can be replicated in future work. These guidelines were implemented straight away in new projects with my guidance.