Benchling

Customer Success Manager

San Francisco, CA, Remote. Posted 22 days ago

The role

Customer Success Managers help customers enhance the value of their Benchling investments. You will advise customers, develop processes, and drive execution by understanding customer science, business goals, and Benchling deployment.

What you will do

  • Dive deep into customer usage data to uncover patterns, opportunities, and risks.
  • Create and execute product telemetry programs.
  • Become the go-to advisor on the Benchling platform.
  • Get to know customers' science, industry trends, and big goals.
  • Collaborate with Sales, Product, and Professional Services.
  • Drive projects like customer journey mapping and voice-of-customer feedback.
  • Own and deliver Executive Business Reviews (EBRs).
  • Design, test, and launch adoption campaigns.
  • Drive deployment health checks, adoption plans, and digital maturity programs.
  • Carve out a niche in specific Benchling product modules or research verticals.

Required qualifications

  • BS or M.Sc in Biology, Molecular Biology, Genetics, Biotechnology, Bioengineering or similar Life Science field, OR 2+ years work experience with Life Sciences or Healthcare companies, ideally in a la
  • 4+ years of Customer Success, Professional Services, or Consulting experience in a SaaS software environment
  • Ability to forge relationships with users, decision makers, and influential stakeholders
  • Strong analytical skills with experience leveraging data insights
  • Strong project management skills
  • Excellent communication skills in verbal, written and presentation formats
  • Self-motivated, independent, adaptable, and can thrive in a fast-paced startup environment
  • Ability to travel 20-30% based on customer needs

Nice to have

  • hands on implementation experience

Before you apply

  • you'll complete a brief AI-focused exercise or discussion

About the company

Benchling is the AI platform for biotech R&D. Scientists use Benchling to design experiments, capture structured data, and run AI agents and models directly in their workflows.