Do you really need a data scientist for your startup?

Throughout my career, I have placed a lot of data scientists at smaller companies. Most of the people placed left within a year of starting with the common feedback that the work didn't warrant having a data scientist.

In most cases a data engineer is more than sufficient to build the organization. Sure AI and machine learning may be critical to your business but the question that should be asked before anyone is hired.

Guest Bio:

Asim Razvi has been focused on Business Intelligence for the last 20 years. He leads the analytics and data strategy for high growth companies.  Asim brings a wide background across Media, Communications and Finance and has built Business Intelligence practices for PwC, Cognizant and Accenture.  

Formerly the Head of Education and Research for TDWI where his focus was to rebuild the TDWI brand through alignment with Analytics, Big Data and Cloud thought leadership.


  • Why to think twice before hiring a data scientist
  • How to hire once a need is established

Challenge today?

  • Why hire a data scientist?

    • Hiring company
    • Think they need AI & ML
    • Its a trademark
    • Organization set up for a data scientist
      • Organization 
      • Data maturity
  • Data Scientist
    • Build something valuable 

      • Not a subject matter expert on what the company wants
      • Insights that drive the company
      • Needs to be linked to the business level

Why is this important to the company?

  • Knowing when to hire a data scientist

    • Monetize data
    • Most companies don't need data scientists.
    • Data analyst - subject matter expert 
    • Provide the relevance

Rick’s Nuggets

  • Not enough challenging work

How do we solve the problem? 

  • Focus on data maturity

    • Sophisticated business users
    • Want business user to become information explorer - drill down
    • Power user- pair with analyst
  • Organization
    • Vertical chain
    • Data scientist working in the sweet spot- co-creation feedback loop
  • Readiness assessment
    • How prepared is the organization to hire a data scientist
    • Do I have the “track”?
    • Data engineer on board
  • Hire or use a Tool
  • Data robot 
    • Enable users to become data scientists
    • Predict algorithms that work
  • Hire
    • You don't need a data scientist as a startup
    • Learning - neural net capability

Key Takeaways that the Audience can plug into their business today! (Value):

  • Don't hire earlier than you need to
  • Remember you need data for a data scientist to work
  • The Business needs to be mature enough in data to hire the data scientist
  • Make sure there is a career arc for the data scientist to grow in the organization

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