UI / UX Design
Mindzie
Redesigned an existing data platform under tight deadlines by collaborating closely with data science, engineering, and sales teams, while balancing UX, project coordination, and QA responsibilities.
Year :
2022
Industry :
B2B | Process Mining
Client :
Mindzie
Role
UX Desginer
About the Project
Mindzie is a process-mining and analytics platform where data clarity and neutrality are critical. I joined the team during a high-pressure phase, tasked with redesigning the platform in preparation for securing a major client. The work required rapid iteration, cross-functional collaboration, and careful consideration of how data was structured and presented.
Key Contributions
Redesigned the existing platform to meet aggressive timelines tied to client acquisition
Collaborated directly with data scientists, CTO, developers, and sales teams
Designed data visualizations and structures with a focus on neutrality and bias avoidance
Acted across UX, project management, and QA roles to support rapid feature delivery
Designed with development constraints in mind to minimize technical debt
Supported feature implementation and demos for prospective enterprise clients
Achievements
Platform redesign delivered under client-driven deadline
New features implemented and demo-ready for enterprise prospects
Improved data presentation with bias-aware UX patterns
UI / UX Design
Mindzie
Redesigned an existing data platform under tight deadlines by collaborating closely with data science, engineering, and sales teams, while balancing UX, project coordination, and QA responsibilities.
Year :
2022
Industry :
B2B | Process Mining
Client :
Mindzie
Role
UX Desginer
About the Project
Mindzie is a process-mining and analytics platform where data clarity and neutrality are critical. I joined the team during a high-pressure phase, tasked with redesigning the platform in preparation for securing a major client. The work required rapid iteration, cross-functional collaboration, and careful consideration of how data was structured and presented.
Key Contributions
Redesigned the existing platform to meet aggressive timelines tied to client acquisition
Collaborated directly with data scientists, CTO, developers, and sales teams
Designed data visualizations and structures with a focus on neutrality and bias avoidance
Acted across UX, project management, and QA roles to support rapid feature delivery
Designed with development constraints in mind to minimize technical debt
Supported feature implementation and demos for prospective enterprise clients
Achievements
Platform redesign delivered under client-driven deadline
New features implemented and demo-ready for enterprise prospects
Improved data presentation with bias-aware UX patterns
UI / UX Design
Mindzie
Redesigned an existing data platform under tight deadlines by collaborating closely with data science, engineering, and sales teams, while balancing UX, project coordination, and QA responsibilities.
Year :
2022
Industry :
B2B | Process Mining
Client :
Mindzie
Role
UX Desginer
About the Project
Mindzie is a process-mining and analytics platform where data clarity and neutrality are critical. I joined the team during a high-pressure phase, tasked with redesigning the platform in preparation for securing a major client. The work required rapid iteration, cross-functional collaboration, and careful consideration of how data was structured and presented.
Key Contributions
Redesigned the existing platform to meet aggressive timelines tied to client acquisition
Collaborated directly with data scientists, CTO, developers, and sales teams
Designed data visualizations and structures with a focus on neutrality and bias avoidance
Acted across UX, project management, and QA roles to support rapid feature delivery
Designed with development constraints in mind to minimize technical debt
Supported feature implementation and demos for prospective enterprise clients
Achievements
Platform redesign delivered under client-driven deadline
New features implemented and demo-ready for enterprise prospects
Improved data presentation with bias-aware UX patterns