Principal Applied Scientist
Roman Health Pharmacy LLC
Auckland, New Zealand
4d ago
source : Jobg8 Ltd.

We're looking for a candidate for this position in an exciting company.

  • Provide leadership to cross-functional teams that build web-scale ML-inside products
  • Work with your peers and the Data Leadership Team to define the roadmap for Applied Sciences
  • Identify cross-cutting opportunities to create frameworks / tooling
  • Work with other scientists to figure out the best practices for reproducible and robust science
  • Keep up-to-date with the latest developments in ML, identifying opportunities for Xero to improve #beautiful products
  • Be comfortable with pushing the frontiers of ML in the pursuit of delivering products, but only where absolutely necessary
  • Make sure our work is always in the best interests of our customers
  • Align multiple programs of work so that they benefit each other
  • Identify new ML product opportunities and work with product teams to determine if they're worth pursuing
  • Create the culture that means people love working with us
  • Mentor, manage, and develop other scientists and colleagues
  • You have extensive experience delivering production machine learning systems
  • You rejoice in identifying tough problems that can be solved with scientific thinking
  • You understand that solving worthwhile problems means covering all areas of the data lifecycle - finding it, understanding it, experimenting with it, despairing over it, fixing it,
  • You're comfortable reading ML research papers, keep abreast of new work on and have on occasion spent your time tinkering around with that interesting new framework you read about recently .
  • but when it comes down to it, you want to solve real business problems in the simplest and most robust way possible
  • You're comfortable working with experts from all corners of the company to deeply understand the customer problem before getting your hands dirty with all that data and code
  • Experience as a hands-on practitioner building productionised machine learning pipelines which touch real human end users
  • You have a solid grasp of statistics and you have wrestled with the challenges inherent in actually measuring the impact of your machine learning pipelines in the wild
  • You've learned through experience that it's important to write testable, repeatable code so you can debug it when something goes bump in the night
  • You know your way around the 'nix command line, ssh your way happily around your multiple running AWS instances and are a competent programmer in Python, Scala or similar
  • You've mentored and grown teams of applied scientists, teaching the skills of scientific reasoning, collaboration, and effective program delivery
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