Head of Data Science at Intechnica, Tom Matcham joins Wendy this week on Would You Data Scientist to talk about his work, how he got into data, the difference between C and C++, and video games. Find out Tom's advice for dealing with frustration, how to get hired in data, and how a degree in data might not actually be as helpful as you'd think. 

KEY TAKEAWAYS

• Tom's favourite piece of tech is the programming language C. He doesn't get much of a chance to use it anymore but he loves the responsiveness and simplicity of it. It's like being as close to the hardware as you can be. 
• Tom had a dream to start a business for video game designers so they could make adaptive experiences via pre-built machine learning tools which he started while he was doing his masters. He entered a competition through Imperial College for funding and won. 
• As a hiring manager Tom doesn't believe that you need a masters to pivot into being a general data scientist. If you want to go into something highly specialised having one in that topic would be an advantage, but for more broad jobs it's not a necessity. 
• A data science degree could even be detrimental to your development according to Tom. He believes the curriculum doesn't focus enough on the problems you face day to day in data. He also believes there is far too much of a focus on statistical distributions that just don't make sense in the real world. 
• Tom recommends the textbook  Statistical Consequences of Fat Tails: Real World Pre Asymptotics, Epistemology, and Applications by Nassim Nicholas Taleb. 

BEST MOMENTS

‘You don't make the same mistakes twice' 

‘It took me of 5 years of bashing my head against a wall' 

‘9 out of 10 businesses that hire data scientists, so not use them in any capacity'

‘There's nothing scientific about data science at all'

VALUABLE RESOURCES

Statistical Consequences of Fat Tails: Real World Preasymptotics, Epistemology, and Applications

Jai programming language

Tom on LinkedIn

linkedin.com/in/ethicalrecruiter

qwerkrecruitment.com

@qwerkrec on socials

ABOUT THE GUEST 

Tom is an experienced data scientist with considerable expertise in commercial research and data analysis. Extensive knowledge of consumer analytics for apps, websites and video games; developed novel algorithms for the analysis of event data. Wide range of skills that covers every step of the data science process - from collection, ingestion and cleaning to advanced analysis, modelling, low-level optimisation and deployment. An adept programmer with considerable knowledge of six programming languages and expert level knowledge of Python, R and C. Three years' experience bootstrapping data science startups to revenue-generating software.

ABOUT THE HOST

Wendy Gannon started Qwerk Recruitment in the middle of the Covid Pandemic to disrupt the recruitment sector with ETHICAL data recruitment and treat everyone with love, dignity and respect. Avid Music photographer of 15 years.

PODCAST DESCRIPTION

Interviewing successful Data Scientists to find out about their journey into Data Science and any struggles they've faced to help next generation Data Scientists from all walks of life to access their dream career.

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