The Complete Beginners Guide to Project Management for Data Science Projects

By Amith Ashokan
Sep 29 10:00 (EDT)


What does Project Management have to do with Data Science? As businesses seek to leverage data to improve operations, Data Science continues to assume a position of greater importance. Traditional Project Management methodologies might not always be well-suited to managing Data Science projects; the solution lies in Agile Project Management. Data science projects tend to become more extensive and complicated than initially planned. That’s where Agile Management comes to the rescue, by helping you avoid scope creep. 

Join us for this engaging session with Amith Ashokan – a cross-functional transformation advisor with more than 20 years of experience – will walk you through the core concepts of Agile Project Management and how we can use it to manage data science projects effectively. First, we help you understand the elements of the data science project scope and best practices and then move to the Beginners Guide to Agile Project Management for Data Science projects.

Key Takeaways:  

  • Data science project lifecycle 
  • Must have skills as a data analyst and data scientist 
  • Measures of data science-driven organizations 
  • Use case for management 


Amith Ashokan

Amith Ashokan


Amith Ashokan is a Cross-Functional Transformation Advisor with 20+ years of qualitative experience in Consulting and Implementation. He has experience in managing critical global projects, served as a mentor for premium universities, and has been an evangelist for Finance and Project Management with Data Science.

Amith has been a speaker and advisor to the board of directors and has an excellent track record of delivering technology initiatives and domain expertise to Fortune 500 clients.

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