Data Science Lead

Health | London

About The Role

As a leader of the Flo team, you will be responsible for guiding and growing the team working within our strategic domain -- health. It is at the heart of Flo, where the team of Machine Learning Engineers work on the toughest challenges in women's health. You will be responsible for the end-to-end ownership of ML problems for the health stream, by delivering more accurate, more personal and more explainable solutions for women’s health issues. In this role you are respected and appreciated by the ML engineering team as a leader. This role reports into the Head of Data Science and is highly visible within Flo.

 

Main responsibilities 

  • Lead the team of 5-7 ML Engineers.
  • Contribute to the product ML strategy and the roadmap.
  • Ensure effective collaboration with product & engineering teams. 
  • Find the right balance between research, product, and infrastructure work.
  • Solve difficult, non-routine analysis problems.
  • Develop comprehensive knowledge about data structures and metrics, advocating for changes for product development.
  • Drive and maintain high-performance engineering culture within the team.
  • Evangelize ML across Flo.
  • Involved hands-on where you deem appropriate.
  • Maintain the collaborative relationship with our technology partners and external experts.

 

Basic Qualifications

  • 5+ years of relevant experience in any combination of leading technology teams and working on machine learning problems.
  • Demonstrated experience in machine learning, deep learning or related fields.
  • Solid understanding of the ML fundamentals.
  • High-performance engineering mindset and experience working with the brightest engineers in the field.
  • A background in computer science or a closely related engineering discipline.
  • The ability to communicate complex ideas effectively with technical and non-technical team members alike.

 

Preferred Qualifications

  • PhD in computer science or a closely related engineering discipline.
  • Experience at the tier 1 product company or related experience working within the product organization.
  • Experience with the ML adoption in regulated industries (finance, health).
  • Experience with the health domain.