Jonathan Chen

Director, AI Applications, Context, & Experience - BT Architecture & AI at Workday | Berkeley Haas MBA

Pleasanton, California, United States

About

Jonathan Chen is Director of Enterprise AI/ML Solutions at Workday, where he leads the development of AI and analytics products that help business analysts work more effectively. A key focus of his team's work is MIDAS, Workday's internal AI-powered analyst agent, which enables business analysts to ask natural language questions and receive accurate, governed insights from certified data products. With a background spanning both technology and business, Jonathan has led Advanced Analytics teams supporting Revenue Operations and Marketing, giving him a strong foundation for connecting data capabilities to real business needs. He holds an MBA from UC Berkeley's Haas School of Business.

Experience

  • Workday (7 yrs 8 mos)
    • Director, AI Applications, Context, & Experiences
      May 2026 - Present · 3 mos

    • Director, Enterprise AI/ML Solutions - Enterprise Data & Analytics
      Feb 2025 - May 2026 · 1 yr 4 mos

    • Director, Advanced Analytics - Revenue Operations
      May 2021 - Feb 2025 · 3 yrs 10 mos

  • Manager, Global Insights and Analytics at Cisco
    Jun 2013 - Dec 2018 · 5 yrs 7 mos

    Global Lead - Marketing Operational Insights and Analytics - Led optimization of Cisco's B2B go-to-market strategy across the demand waterfall focusing on marketing insights, optimal marketing investment modeling, and rapid experimentation. - Built and currently directing a global testing and optimization organization in center-of-excellence model, with team suggesting, executing, and analyzing results of major tests on web pages serving 100m+ unique visitors annually. - Leading digital strategic planning and goal setting using market potential and competitive data to drive focus and initiatives for Cisco’s major campaigns spanning enterprise networking, data center, collaboration, and brand. - Designed global inbound marketing strategy for Cisco focusing on paid, owned, and earned channels, delivering results over $750m annually in inbound sales qualified leads for Cisco and partners. - Introduced and established a framework for measuring and predicting customer engagement across omni-channel experiences, highlighting opportunities to improve customer loyalty and revenue. - Coordinated and socialized efforts from various teams by joining reporting from Adobe Analytics, contact centers, and Salesforce.com into DOMO to develop an end-to-end view of the demand pipeline. - Delivered dashboards, in-depth insights and analysis from business intelligence tools such as DOMO and Tableau to optimize marketing performance generating increased customer acquisition and improving the revenue pipeline. - Presented best practices to external and internal audiences through speaking engagements with Haas School of Business and Norwegian School of Business (BI), in addition to Cisco’s marketing organization of 1000+ employees.

  • Senior Manager - Marketing at QuinStreet
    2009 - 2013 · 4 yrs

    - Led online marketing strategy, media budget, and analytics for two verticals delivering revenues of $10m annually. - Established PPC campaigns focused on maximizing return on investment for multiple monetization models (CPM, CPC, CPA/CPL) in both a direct marketing and in an agency of record approach. - Increased overall marketing campaign margins by 20+ percentage points through aggressive optimization and bid management, as well as dayparting, adcopy creation, conversion tracking, and landing page A/B testing. - Enhanced campaign quality and efficacy by integrating Google Analytics and conversion optimization tools with day-to-day campaign management, resulting in increased quality for clients and fewer returned leads. - Created reports for executive management summarizing entire paid search media performance using SQL/Excel, including macros to segment data by vertical, advertising platform, and search vs. display.

  • Process Development Engineer at Spansion
    2004 - 2009 · 5 yrs

    - Developed strategy and experiments to optimize results for research and development projects, leading to major yield improvement. - Increased speed for identification of issues by designing data mining systems through SQL/MS Excel to highlight defect trends, resulting in reduced engineering time by 8x. - Designed classification algorithm with large-scale database to clearly identify relevant data and determine significant risk factors to production resulting in mitigation of production risk.