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Daniel Fudge

Director of ML and Data Engineering

Toronto, Ontario, Canada

Daniel leads the data science discipline in Very’s Data Solutions department. Driven by ownership, clarity and purpose, Daniel works to nurture an environment of excellence among Very’s machine learning and data engineering experts — empowering his team to deliver powerful business value to clients.

photo of Daniel Fudge Director of ML and Data Engineering
photo of Daniel Fudge Director of ML and Data Engineering


For more than 20 years Daniel has worked on diverse and complex engineering and advanced analytics projects. He previously focused on aerospace engineering before switching to optimization, data engineering, and machine learning.


In previous roles, Daniel enjoyed digging deep into the details to learn how systems truly work, and then finding the optimization opportunity that would have the highest impact for the business. This inevitably placed Daniel in a multi-disciplinary role where often the most difficult and critical system to optimize was the group. This led Daniel to his MBA, and now to Very.


  • Master of Business Administration, Financial Engineering, Schulich School of Business in Toronto
  • Master of Applied Science, Computational Aerodynamics, University of Toronto
  • Bachelor of Applied Science, Aerospace Engineering, University of Toronto


In the cloud arena, Daniel’s a huge fan of serverless architectures, IaC, containerization and micro-services. For software development, he believes in test-driven design, extensive unit testing and automated CI/CD as the basis for all great code.


Daniel relies on a number of frameworks and languages, including:

  • Python
  • PyTorch
  • AWS
  • C++
  • TensorFlow
  • Elixir/Phoenix


When he’s not busy learning a new software program or creating solutions for Very clients, Daniel enjoys playing ice hockey, jogging, hiking, boating, sailing, and completing home renovations.

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