Field Engineer at Domino Data Lab

| San Francisco
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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.

Field Engineers are an elite team who help data science teams turn their companies into model driven organizations. Field Engineers deploy Domino’s software, train users, re-develop team processes, integrate data sources, and customize tools.

As a Field Engineer, you’ll work across a wide of array of problems and a diversity of industries. One day you might be helping a marketing company starting to work with satellite images or an insurance company get money to their customers faster by integrating NLP into their claims processing. You’ll be training a room full of new users or sitting with an individual data scientist helping them get the most out of Domino.


Responsibilities:

  • Responsible for working with Domino’s most strategic customers to ensure their success
  • Build integrations to support custom/advanced Data science workflows and how they integrate with the Domino API
  • Play an advisory role to our customers to help leverage domino and data science best practice.
  • Actively commit to our knowledge base to evolve the way customer success operates at Domino.
  • Help evolve the way domino deploys and maintains our software by being in constant communication with core-development

Qualifications :

  • Excellent troubleshooting skills
  • Strong interpersonal and communication skills
  • Willingness to travel up to 40% of the time
  • Deep experience with system architecture (preferably in both AWS and on-prem environments)
  • Programming experience (Python or R preferred)
  • Knowledge of data science workflows
  • Understanding of Data integrations 
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