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Recruitment BlogOptiver Graduate stories: Pathways to a career in Research
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Optiver Graduate stories: Pathways to a career in Research

February 11, 2022

Noah Peres
Options Research

What attracted you to apply to Optiver?
At first it was the friendliness of the Recruitment team, who I met at a careers fair. After that it just got more and more fascinating as I hear about the maths and probability behind the trading problem – potentially unbounded complexity and a fascinating puzzle.

What team do you work in and what are they responsible for?
I’m in the Options Pricing Research team. We are responsible for leveraging historical and live data to iterate upon and improve the options prices that we show the market. In close collaboration with Trading, we develop models and projects to provide tools for traders to apply and integrate into their systematic position taking.

Describe an interesting project?
Currently I’m managing a project on positional allocation for one of our teams. When they often trade hundreds of instruments at a time, it can be very tricky to know the optimal position allocation between the instruments beyond gut feel/experience. We feel this is a key area where there is opportunity for a data-driven approach to have huge impact, and it is great to be given this opportunity so early in my career.

What keeps you motivated?
There are always problems and projects which need attention – the job is never done for us in Research. Pretty much every one of these problems has some interesting maths behind it and it can be very rewarding to see the concrete impact of your work on the company. The support provided by Talent and my team management is also second to none.

What was your training like?
The training program was very cohesive, comprehensive, and really builds your industry knowledge base from the ground up. Optiver made a great effort to make the program accessible to those not from a finance background. The Head of Education would give us detailed and fascinating explanations of key concepts, and we would immediately get to go and apply them to the simulations, projects, or discuss them with the experienced traders on the floor during the many trader shadowing opportunities. Importantly, the program was just an enjoyable time – plenty of healthy collaboration and friendly competition from within the group creates a positive environment to expedite the learning process.

What do you love most about your role/Optiver?
I love getting to see some of the more niche maths I learned at university have a direct measurable application to a ‘real world problem’.  For example, concepts such as stochastic analysis, time series analysis, statistical inference often when taught at university can be hard to see how they apply to the world outside of the abstract. This is just one of the rewarding and fascinating things you get out of working at Optiver.

If I could pick a second thing it would be the people – I am yet to meet someone who isn’t respectful, intelligent, driven and fun to be around. You always look forward to going to work if only to catch up with your team!

Do you have any tips for graduates going through the process?
Perhaps the big tip I can give is never to settle – even once you have made it through the process you need to keep that drive alive, and hit the ground running to get the most out of Optiver.


Nik Mather
Researcher | Delta 1 – Base Trading

What attracted you to apply to Optiver?
Optiver has a good reputation on campus and I had a friend who was really enjoying their role here already! I was very impressed by the people who interviewed me, and although I hadn’t pictured myself working in finance before this, I found the role to be a great fit for me. 

What team do you work in and what are they responsible for?
I work in the Delta 1 tribe, on Japan Base Trading – we’re responsible for pricing and trading Japanese stocks and indices.

Describe your current role?
My role revolves around building statistical models to make predictions for where prices are going to go. We have a heavy focus on machine-learning based models, so I spend a large part of my time building hypotheses about how the market functions, testing them, then finding ways to abstract those findings so they can be incorporated into our models.

I’m also responsible for optimising our machine learning processes – finding improvements to the way we build models that will let us use the information we have more effectively.

What keeps you motivated?
I’m motivated by learning new things and at Optiver there’s always interesting challenges. I’m excited by the opportunity to take on projects involving problems I haven’t seen before, which require me to pick up new knowledge before I can tackle them.

What was your training like?

For me, it was an opportunity to find my niche within the company. Optiver does a lot of different things, each of which requires different skills. During training, we were exposed to several areas, and I could figure out what I enjoyed and where my background aligned to. Optiver ensures that you’re in the right role for you.

What do you love most about your role/Optiver?
Two things stand out. First, I get to interact with clever, knowledgeable people every day. I’ve learned a lot and found new passions by working closely with people who have different backgrounds and skillsets to me.

Second, I get to use all my technical skills and theoretical background to solve real problems. The theory of machine learning is fascinating by itself, but it’s extra satisfying using it to build models that achieve quantifiable results.

Do you have any tips for graduates going through the process?
It’s worthwhile having a clear vision of why you want the role. It might help to articulate that to yourself first, then in the interview – what you find interesting and why, and how that maps to what Optiver does.


Rob Newey
Performance Researcher

What attracted you to apply to Optiver?
In high frequency trading, the competitive market means the problems you solve can’t stay the same – they keep getting harder, and you have to keep challenging yourself. I find this incredibly motivating, and the team at Optiver is so open and collaborative – it’s the best environment to solve hard problems in!

What team do you work in and what are they responsible for?I’m in the Performance Research team, who focus on execution, speed and success. Identifying profitable trades to make is only one part of the process. Once that has happened, you have to execute. In order to execute the best, my team analyses and theorises about everything from low level systems and networking protocols, up to higher level trading algorithm strategy optimisations.

Describe your current role?
My current role is focussed on statistically analysing the exchange system from a networking/OS level. I take an understanding of what all our trading systems are trying to accomplish, get really into the minutia of the networking data we’ve captured and theorise about what’s happening in this exchange “black box”. I’ll come up with experiments to test these theories, and if there are improvements, I’ll work with Traders and Developers to get the results into production.

What keeps you motivated?
The rush of those ‘eureka’ moments can be addictive – where everything clicks into place. It’s challenging, and sometimes it’s a long time between. But it’s all worth it when you get the satisfaction of really figuring something out.

What was your training like?
I’ve been here for over two years and I still feel like I’m in training (in a good way) – you will never know everything! When I joined, I had a lot of team support, help with dissecting what I found, and how that related to Optiver’s systems.

What do you love most about your role/Optiver?
Most? Now that’s a hard question. I love that I have the autonomy to focus on problems that I will have the most impact on. We’re all on the same team, and when people are able to do their best, Optiver does its best.

Do you have any tips for graduates going through the process?
Most importantly, apply! The worst way to miss a good trade is to not shoot for it! Secondly, not knowing everything is okay, take time to show what you are good at. Also, try to be concrete when talking about how you would approach a problem. The role is about taking large abstract problems, breaking them down, and actually doing the work to solve them. We want to see that you can break a problem down to the point where you can articulate the actions you will take to solve it.

If you’re excited at the prospect of joining our graduate program, applications are now open for 2022-23.