Project Manager at Domino Data Lab

Domino Data Lab

Project Manager

  • San Francisco or Remote

Domino is helping the world run on models. Data Science teams at model-driven companies use our platform to accelerate breakthrough research, increase collaboration, and rapidly deliver high-impact models. Our customers are sophisticated analytical organizations including Allstate, Dell, and Bristol-Myers Squibb. Backed by Sequoia Capital, Zetta Venture Partners, Bloomberg Beta, and Coatue Management, we are at the epicenter of the data science revolution: helping companies build better cars, develop more effective medicine, or simply recommend the best song to play next.

We are seeking a Project Manager to join our Customer Success team and assist our customers in new deployments and upgrades. Responsibilities and qualifications are as follows:


  • Ensure a successful and positive end-to-end experience for legacy customers upgrading from Domino 3.x to Domino 4.x
  • Manage customer upgrades and new deployments in a variety of technically complex settings
  • Collaborate with internal stakeholders at Domino in Customer Success and Engineering as well as external stakeholders at our customer organizations
  • Customize upgrade plans for each customer; Identify and mitigate risks early on; Track and resolve issues with the help of a QA team member; Communicate clearly with all stakeholders throughout.
  • Act as the point person for assigned customers; Understand the high level project vision as well as each milestone


  • 3-8 years of experience leading projects of a technical nature for enterprise clients in financial services, healthcare, insurance, etc.
  • Customer-facing skills required; Clear written and verbal communication
  • Ability to manage multiple projects in unique circumstances simultaneously
  • Thrives in a dynamic startup environment
  • Anticipates roadblocks and can proactively fill in gaps as needed
  • Exhibits adaptability, creativity, and perseverance
  • Exposure to/interest in the world of data (BI, ETL, SQL, or Data Science) is preferred

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