Listen to this episode on Anchor FM
This episode of DATAcated on Air is a double topic from guest Ken Jee, Head of Data Science at Scouts Consulting Group. Host Kate Strachnyi talks with Ken about his experience breaking into data science and sports analytics. Ken is a remarkable data scientist and YouTuber. Listen to learn more about the relationship between data science and sports analytics.
You will want to hear this episode if you are interested in...
- A broad view of data science [04:13]
- Platforms to start problem-solving [06:09]
- The backbone of data science [12:58]
- Breaking into sports analytics [16:32]
- Employee referrals without experience [25:13]
- What is sports analytics? [29:16]
- Alternate routes to being successful [38:27]
- Market opportunities in sports analytics [46:38]
Determining where to start
One of the most challenging things about data science is that the field is so broad, with many elements of programming, math, and creating business value. Data science can seem highly overwhelming from the outside because there’s so much to learn. Narrowing the scope and breaking down data science into various categories will lead to successful learning in this field.
Ken suggests that people first start learning to program, specifically Python. While the math concepts are also important, those can be learned a little later. After learning some foundational programming, focusing on problem-solving and beginning projects is the next step. This process takes data science from an overwhelmingly broad category into a reasonably concrete, finite concept of understanding the problems.
Increasing your odds of being hired
While obtaining a job is in many ways a numbers game, some factors can be affected to increase odds. For example, going through an employee referral skyrockets odds compared to going through a resume drop. Referrals take more time, but that’s an opportunity cost of the time that would’ve been spent just sending out resumes. Taking this approach helps people look forward and think about how they can better themselves to increase their chances of being hired.
One of the most important things is the storytelling aspect of a resume. It should tell the story of how everything up until that point has brought someone to an interview. The next logical step through that conversation should be a job offer. Ken talks more about those soft skills on his YouTube channel.
The future of sports analytics
With sports gambling becoming legal, many market areas will open up. People will be able to place bets on every shot in every minute of a game in almost real-time. There’s an opportunity for arbitrage on the gambling side. There will also be a lot of opportunities in data collection and understanding the psychology of performance. There aren’t as many resources available for understanding the non-physical aspects of the game right now.
In the future, athletes might be willing to share health data more. Right now, athletes are scared that data will be used against them. However, many things can be done with that biodata to make sports safer. Data would help better decisions be made. On the performance side, players could be given optimal rests to limit injuries and be stressed the exact right amount during practices. There are many incredible opportunities on the data collection side.
Resources & People Mentioned
- #66DaysOfData | KennethJee
- AndrewMoMoney - YouTube
- Chai Time Data Science - YouTube
- Playing Numbers
- Mathletics: How Gamblers, Managers, and Sports Enthusiasts Use Mathematics
- Nylon Calculus news
- How to Start a Career in Data Science 2022 | Udemy
- Oura Ring
Connect with Ken Jee
Connect with DATAcated
- DATAcated on LinkedIn: https://www.linkedin.com/company/datacated1/
- Kate on LinkedIn: https://www.linkedin.com/in/kate-strachnyi-data/
- DATAcated on Twitter: https://twitter.com/datacated_
- DATAcated on YouTube: https://www.youtube.com/datacated