DataTalks.Club

Product Management for Machine Learning - Geo Jolly

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We talked about

  • Geo’s background
  • Technical Product Manager
  • Building ML platform
  • Working on internal projects
  • Prioritizing the backlog
  • Defining the problems
  • Observability metrics
  • Avoiding jumping into “solution mode”
  • Breaking down the problem
  • Important skills for product managers
  • The importance of a technical background
  • Data Lead vs Staff Data Scientist vs Data PM
  • Approvals and rollout
  • Engineering/platform teams
  • Data scientists’ role in the engineering team
  • Scrum and Agile in data science
  • Transitioning from Data Scientist to Technical PM
  • Books to read for the transition
  • Transitioning for non-technical people
  • Doing user research
  • Quality assurance in ML
  • Advice for supporting an ML team as a Scrum master


    • Links:

    • Geo's LinkedIn: https://www.linkedin.com/in/geojolly/
    • Product School community: https://productschool.com/
    • http://theleanstartup.com/ 
    • Netflix CPO Medium blog: https://gibsonbiddle.medium.com/
    • Glovo is hiring: https://jobs.glovoapp.com/en/?d=4040726002


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