#80 Rising Through the Ranks in Data Science with Nufar Gaspar – Data Science Vertical Manager

Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

Nufar Gaspar is a Data Science Vertical Manager at Intel focusing on creating a machine learning and big data solutions for the various R&D teams at Intel. The teams in her vertical create a vast range of data-science solutions on Hadoop and Spark-based platforms. The range of their solutions spans running algorithms to compile test lists to optimize resource consumption vs. test quality; solutions for finding hidden CPU bugs; through adv. methods to automate debug process and more. They use a variety of data science techniques from "classical" machine learning and pattern recognition techniques, through optimization & NLP techniques to deep learning and reinforcement learning, and more. Her organization includes teams of data scientists, big data SW developers, and AI specialist's product managers and analysts.

Enjoy the show!

We speak about:

• [02:00] How Nufar started in the data space
  
• [10:30] Nufar began to train new engineers
  
• [21:50] Focusing on bringing solutions to production
  
• [24:20] How Nufar picks what to work on
  
• [27:15] Putting algorithms inside Intel’s products
  
• [32:00] The infrastructure behind Intel’s machine learning
  
• [40:30] Returning to work after maternity leave
  
• [43:30] Women in Big Data
  
• [47:50] What excites Nufar most about data science
  
• [49:30] Advice for listeners
  

Resources:

Nufar’s LinkedIn: https://www.linkedin.com/in/nufar-gaspar-76b7424b/

Nufar’s Talk: https://www.youtube.com/watch?v=cx_2wAP40-g

Women in Big Data: https://www.womeninbigdata.org

Quotes:

• “You have to understand the different business processes.”
  
• “We are doing a complete business process redesign from scratch.”
  
• “For us to maintain our leadership position in AI, we have to continue running as fast as possible.”
  
• “Before I left for maternity leave, I had to negotiate with my managers to determine what position I would have when I return.”

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