Pavel Pleskov – Data Scientist & Kaggle Grandmaster

Pavel Pleskov.jpg

Pavel Pleskov is a data scientist at Point API (NLP startup) and currently ranks number 3 out of 109,624 on Kaggle, making him a Grandmaster. Pavel has started companies in the past and has worked in many different industries before becoming a data scientist and Kaggle Grandmaster.

In this episode, Pavel explains his background and how he started in the data science space. When Pavel’s girlfriend went to pursue her master’s degree in London, Pavel began interviewing for a quantitative research job nearby. Turns out, the company was a rival of his current employer, causing him to get fired from his job the next day. Former employees of this job contacted Pavel to ask if they would join their new trading firm and be head of their research team. After doing his job for two years, Pavel knew he was capable of doing it on his own. The company works remotely, and after spending time in bitter Russian winters, Pavel looked to work elsewhere. The ideal country turned out to be Vietnam and was Pavel’s first time outside of Russia.

Then, Pavel started taking machine learning courses and found the platform Kaggle to practice what he has learned. Practically, Kaggle is much more helpful than homework or any online course. The most significant part of his success was spending full-time on Kaggle rather than working another job. Then, Pavel explains the difference between machine learning engineers and researcher data scientists. Later, Pavel reveals his intention behind becoming the very best at his work. The key to success is to find something you like and become the very best at what you are doing. If you are doing something that you do not enjoy, then there is no way you will become the very best. The only way to overcome your obstacles is to enjoy what you are doing.


Enjoy the show!


We speak about:

  • [01:50] How Pavel started in the data space

  • [09:50] Vietnam is an ideal space for working remotely and teaching English

  • [21:40] The moment Pavel found Kaggle

  • [24:20] How Pavel became a data scientist

  • [28:00] Difference between machine learning engineers and researcher data scientists

  • [31:50] Why is it essential to be the very best?

  • [34:20] Machine learning and mathematics

  • [36:45] The early days of Pavel’s Kaggle journey

  • [40:00] Pavel’s favorite part of Kaggle

  • [47:20] The role of automation in Kaggle   

  • [49:40] The steps when approaching a new Kaggle competition

  • [52:55] Think twice before you commit to data science


Resources:

Pavel’s LinkedIn: https://www.linkedin.com/in/ppleskov/?originalSubdomain=ru

Pavel’s Kaggle: https://www.kaggle.com/ppleskov

Pavel’s Twitter: https://twitter.com/ppleskov

Quotes:

  • “It is tricky to work remotely as a data scientist.”

  • “It takes a lot of time to find your passion in life. People spend too much time on things they do not enjoy.”

  • “When I first started Kaggle, I entered any competition and tried to improve my score on the leaderboards.”


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Pavel Pleskov is based in Moscow, Russia.


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