Editorial Summary :

For Data Scientists, driving initiative is a common approach to creating impact inside the organization . In this article, I will share my thoughts about the general stages (or components) involved in driving a data science initiative, along with one of my previous projects as a case study . The four-stage model serves as a simple way of conceptualizing the complexity involved, as each permeates across the initiative’s full life cycle . For example, Vision is not only established just at the beginning but also requires constant reinforcement . Vision and Execution not necessarily comes after everyone is aligned but one need to execute on the idea . LinkedIn‘s Data Science New Hire project was a fun experience for students . The initiative aims to build a data product to provide insights for customers . It requires multiple partner teams to be involved, including Engineer teams who create upstream datasets and Insights team to ensure consistent communication on sales message. The initiative is formally established, and we could allocate resources to work on it. It takes quite an effort to get the alignment across and I remember biking across the LinkedIn campus on a daily basis to chat with various partner teams . LinkedIn Learning’s new data product could be a game-changer for higher education institutions to understand student career readiness and curriculum effectiveness . LinkedIn Learning‘s data product was announced at a summit for education institution customers in April 2018, and the feedback was predominantly positive. Subsequently, such insights were incorporated along with our product offerings to better serve LinkedIn‘s mission. For me, it was dream come true: finally, I contributed to the product that helped me in the past. There are so many learnings driving this data science initiative from start to end . Pan is currently a Senior Data Science Manager at Meta Platform Inc. Even after moving to another business organization, he still received “Thank you” emails telling me how insights from our data product win the customer back . Driving initiative is an essential skill for advancing one’s data science career, and I wish this article could be helpful . If you enjoyed reading this article, feel free to spread the word by liking, sharing, and commenting on Facebook and Twitter . You may also follow him on LinkedIn .

Key Highlights :

  • Data Scientists are often more complicated than just writing code to build a machine learning model .
  • Driving initiative involves the following stages (or components) in creating impact .
  • The stages can also be viewed as components as well as components .
  • LinkedIn student: What’s more challenging is knowing what to learn for students with the goal to land a job right after graduation .
  • He says the idea was successful, but it needs sponsorship from the Learning organization .
  • LinkedIn Learning’s data science initiative is now a reality-based data science project .
  • The project manager says proper project management skills are quite practical .
  • Pan is currently a Senior Data Science Manager at Meta Platform Inc. Pan is a Senior data Science Manager .
  • He says driving initiative is an essential skill for advancing one’s data science career .

The editorial is based on the content sourced from medium.com

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