Willis Read-Button

Willis Read-Button is a biomedical professional with extensive experience in genomics and data science. He currently serves as the Director of Project Management for Data, AI & Genome Sciences at Merck, based in Cambridge, Massachusetts.1

Career Progression

Willis has had a notable career trajectory in the field of genomics and biotechnology:

1. Current Role: Director of Project Management - Data, AI & Genome Sciences at Merck (November 2022 - Present)

2. Previous Positions at Merck:

   • Associate Director, Genomics Project Management (June 2020 - November 2022)

3. Entrepreneurial Experience:

   • Co-Founder and Vice President of Operations at Genometry, Inc. (March 2016 - October 2019)
   • Co-Founder and Director of Operations at Genometry, Inc. (August 2012 - March 2016)

4. Research Experience:

   • Research Associate II at The Broad Institute of MIT & Harvard (October 2010 - August 2012)
   • Research Technician I at Broad Institute of MIT and Harvard (September 2008 - October 2010)

Key Achievements and Responsibilities

At Genometry, Willis played a crucial role in:

• Spinning out the company from the Broad Institute
• Building out the laboratory facility
• Designing and optimizing laboratory processes
• Participating in high-level business decisions
• Managing vendor and client relationships
• Leading a team of lab and data employees
• Directing the development of data pipelines and tools for quality monitoring and biological discovery1

During his time at the Broad Institute, Willis:

• Worked on the Connectivity Map Project, developing new gene-expression profiling technology
• Conducted technology development and assay optimization for the L1000 gene-expression assay
• Coordinated efforts between biologists and computational teams
• Managed the production of one of the world's largest gene-expression datasets (over 1 million profiles)1

Willis Read-Button's career demonstrates a strong background in genomics research, data science, and project management, with a particular focus on gene-expression profiling and its applications in drug discovery and development.