Data Science

Meet the Expert: Chief Data Scientist, Chris Pedder

Discover the inspiring journey of OBRIZUM's Chief Data Scientist, Chris Pedder. Learn how Chris's unique path led him to champion a collaborative approach to working with AI.

Meet the Expert: Chris Pedder

We recently caught up with OBRIZUM’s Chief Data Scientist, Chris Pedder, at our offices in Hove. Chris shared with us how his journey to a career in data science wasn’t exactly a linear one, and why working with artificial intelligence should be a collaborative experience, not a substitution.

The Conception and Modern Uses of AI with Dr Chris Pedder

Watch this snippet, or read a short summary in Chris' own words below.


I was born in Nottingham in the 1980s. I grew up in a place where the miner strikes were everywhere, and I saw what that did to communities. It was a really sad time for the Midlands and there were lots of communities that were really decimated by the fact that loads of people suddenly fell out of the working world and there was really no plan to upskill them and to get them ready for a life outside of mining. So that kind of gives you a bit of background as to why education might be important to me.

I was really super lucky to get a scholarship to the local high school. My parents were both computer programmers, so they tried to instill in me early on the importance of being able to code and the importance of how you think and how you structure your thoughts. They always remind me that, for my eighth birthday, they got me an Atari computer, which I think they saved up for for months, and I burst into tears because I wanted a bike. 

So, this was my first missed opportunity of many. I was quite a nerdy kid, and then I went off to do Natural Sciences in Cambridge thinking that I would become a chemist. I did a year of chemistry, discovered I was absolutely terrible at anything to do with practical science and switched very quickly to doing maths. I was lucky enough again to get a studentship to do a PhD in Cambridge. My Ph.D. was in high energy physics and string theory; in 2004, this was super cool. Friends of mine in artsy subjects used to invite me to parties just so they could point to the string theorists in the room.

By 2007, when I finished my Ph.D., the whole wave was collapsing. Everyone was realising that it was not going to be this answer to what's the one underlying physical theory that describes the world? And it turned into a tool. So, actually, I saw first-hand in academia that Gartner hype cycle where something takes off, it gets wildly overhyped, everyone gets really excited about it, and then at some point you tip over the top and that's where the real work happens. 

The switch to coding

I went into essentially using the physics that I learned as a string theorist to do research into material science. I really wanted to nail energy transmission. Green things have always been very important to me. I moved to Switzerland in 2017 and discovered that the funding system for academia in Switzerland was kind of harsh. So, I was already too old to get postdoctoral positions there. I needed to basically either be professor level, which I wasn't, or to go somewhere else, which I didn't want to do.

I ended up switching fields and I discovered that the little bit of coding that I had learned as a physicist was actually pretty transferable to data science machine learning. So I got into this new field. I was lucky enough to have a very supportive partner, so I did an unpaid internship for a company based in Lausanne and then just worked my way up from there.

Advice for budding coders with no previous experience

Writing your first lines of code is always daunting. The key thing is to look for good problems to solve. We all have annoying things in our daily lives that we would like to automate, not have to deal with, you know, have some way of managing automatically. Those are the perfect things to learn to automate. So just simple stuff like if you want to be able to automatically unsubscribe yourself from email lists that you don't read now, just write yourself a simple piece of code that will just go through your Gmail account and unsubscribe. It gives you an opportunity to learn to code practically, which is a good thing to have.

The community aspect is really important as well. This is one of the joys of social networks now. Places like Reddit are really supportive and really helpful, and then there are collaborative tools for sharing code online. They're really amazing for finding people who will support you and mentor you. By and large, software engineers tend to be quite passionate about helping each other out. Same with data scientists.

Collaborating with AI

I would say the right way to think about the new wave of generative AI and the new wave of machine learning models in general is that they're tools. So, the sort of relationship that we should be trying to develop with them is a co-pilot when they're there to speed us up, they're there to help us automate the best work that I referred to before, and they're there to help us be better at the things that are important.

There's a lovely analogy from the world of chess. When Garry Kasparov was playing against Deep Blue in 1997, he lost to the IBM computer and I think he lost four of the five matches that he played, maybe all five. And his reaction to this initially was to feel like a failure and to feel like he had failed to represent humanity against the coming wave of machine learning. He quickly switched and realised that actually it opened up a whole new world of interesting chess play; machines are very good at telling you from a given move what's the most sensible outcome in terms of maximising your chance of winning. But that doesn't include the human aspect of the person that you’re across the board from. So, he developed this idea of centaur chess where you combine a human chess player with a co-pilot, which is a chess engine, and allow the two to play together. 


Chris Pedder's journey from childhood influenced by industrial change to becoming a leader in data science and AI highlights the crucial importance of embracing change and establishing a collaborative relationship with evolving tech.

Whether you're stepping into the world of coding for the first time or looking to refine your project management skills in an AI-driven world, our courses are designed to equip you with the knowledge and tools you need to succeed. Join us on this journey and make the change today.

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