Our innovations begin with the data science team. After all, we’re a data-driven business that lives to explore the possibilities of technology, so we’re creative, take risks and use what we know about our customers to develop the experiences that engage and delight them. Our data experts gather rich insights from our wide customer base and use those to inspire industry-leading features within our apps.
So what does that mean for our teams? Go time! With access to the best tech stack in the data science, machine learning and data engineering space, they’re always coming up with something new and exciting – it’s all in a day’s work here!
Here’s what members of the data science team have to say about working at Sportsbet.
On standout projects the team has worked on...
Mia O'Dell, GM Data Science
We're on a journey of increased personalisation for our customers at Sportsbet, and the pinnacle of personalisation is through machine learning and data science. So much of what we do has a huge impact on the business.
We build models that drive industry-leading app features. We build the core models that drive the odds and prices that our customers can wager on (i.e. what are the odds that the Yankees beat the RedSox tomorrow?) Most importantly, we build the machine learning models that help keep our customers safe from harm.
Kaushik Lakshman, Head of Data Science
The most exciting project I've been a part of so far has been Powerprice, a new and unique generosity mechanic that only Sportsbet offers. It uses ML to predict what bets our customers are likely to make, and offer very generous odds boosts on them.
Our customers love it and tell us they’re amazed that we give them amazing offers on what they love to bet on. Due to the unique nature of our domain, it was quite tough from the data science perspective, so the fact we ended up delivering such a great experience that customers can’t get elsewhere is a fantastic feeling.
To build such a product requires an incredible amount of collaboration, and while this has been challenging, we’ve got a great collection of people who all have a common goal, which certainly made it much easier.
Andre Easom, Head of Data Science
The one that really stands out to me is the launch of Same Game Multi, for AFL. My role was to build the model that powers the pricing.
It was a whole new type of betting experience that we were putting in customers’ hands, so figuring out how to build and test the model came with a range of challenges. Happily, it has been a runaway success with customers, which many competitors have rushed to copy.
I still love using the app to generate prices for all sorts of crazy combinations, knowing it is all powered by a model that I built!
John Hannebery, Data Scientist
I am blessed to have been heavily involved with the world of Safer Gambling. We are industry-leading with our multiple machine learning models that power our approach to Safer Gambling. This enables us to really scale our approach in ensuring customers have a great but safe experience.
The concept of solving Safer Gambling from a modelling perspective is extremely difficult, so we are always thinking about how best to improve our approach. We understand the importance of owning our models once they are productionised, especially for a use-case as important as SG.
A big win was setting up a proper MLOps approach. This includes but is not limited to ensuring data is available for the model to run and make as accurate predictions as possible, and if something goes wrong with the model, we have a system set up so that on-call engineers will be notified and we can solve the problem immediately and collaboratively.
Paul Foerste, Head of Data Science
The first project I ever worked on at Sportsbet, 12 years ago – building an in-depth AFL model.
Prior to this, the AFL offering was a handful of markets that needed to be manually priced by the traders, and once a game was live there was only the ability to offer two or three core markets. This meant that any price changes (due to an injury for example) were extremely laborious.
After a collaborative effort with the AFL traders and developers, we delivered the AFL model, which was the first model of its type in the group delivered from Australia at the time. Once the model was productionised, overnight Sportsbet's AFL offering went from the handful of manually priced markets, to over 200 derivative markets – all automatically priced, with the majority of these available to be priced when the game was live.
It was the first time I had built a model of such complexity so there were definitely challenges and plenty of second-guessing along the way but with the help of colleagues both local and global we were able to deliver a model used by the business for many years.
Qiong Wu, Senior Data Scientist
I love the work that I've been doing in the safer gambling domain. We build cutting-edge models that make sure our customers are betting within their means to maximise enjoyment and minimise harms.
The biggest wins are that customers will know that Sportsbet is protecting them and trust us. The biggest challenges are how we can best balance the amount of control we have while at the same time giving customers enough space to enjoy our products.