Tom is a Quantitative Research Manager at G-Research.
Tom Joined G-Research in 2009 after working for an investment bank. Tom studied Mathematics at the University of Cambridge and Berkeley University before doing several postdocs at various universities in Europe and the US.
How did I become a quant?
Personally, I come from a pure mathematics background. After completing my PhD in the United States, I spent several years doing various postdocs, including two and a half years in London.
At this point I decided to leave academia as I wanted to live in London, since my wife was already working here, and to be frank, I wanted to be able to afford to buy a house!
Also having seen the amount of administrative work and grant applications that were involved in academic careers, and the general level of morale in departments I knew well, I no longer felt excited about academia. I wanted to work in a more collaborative environment and work on more applied projects that would be of interest to more than a handful of other pure mathematicians.
I worked for two years as a front office quant in an investment bank, then I joined G-Research in 2009. At that point the company employed 60 people. Since then it has grown steadily to more than 450 people today.
What skills are required for new quants coming straight from academia?
Nearly all quants working here join G-Research straight from academia, without any previous experience of working in finance. The majority of new quants have PhDs, and many have done postdocs too. In depth knowledge of financial markets is not a prerequisite for new quants, although an interest in finance and the interest and enthusiasm to learn definitely is!
Quant candidates typically come from maths, physics, computer science or engineering backgrounds with an increasing number of candidates come with machine learning and data science skills. Obviously a candidate with a pure maths background will have a different set of skills and way of thinking than an experimental physicist, but both can be equally valuable.
A good level of computer proficiency is essential for quants, as is a willingness to “get your hands dirty” with data. Programming experience in an object oriented language is very useful. Our main in-house language is C# and we are also increasingly using Python. Quants write large amounts of code, but also work very closely with our supporting developers to make sure that code is production-ready.
One difficulty for new quants is the number of in house research tools that need to be mastered. G-Research recognise that the learning curve is quite steep, and for this reason invest a large amount of effort in mentoring and managing new quants to help them through this as smoothly as possible.
In the longer term, in quant research, the same as for any research activity, a great deal of time is invested in ideas that ultimately fail – research is a marathon rather than a sprint – so being mentally prepared for this is essential.
As quants become more experienced, they are expected to increasingly generate their own research projects, and as quants progress further in their career interpersonal, communication and project management skills become more important.
What is the workplace culture, and a typical working day?
Across the company, people are motivated, intelligent, proactive and unassuming. For me one of the biggest positives of working here is my colleagues. There are no fixed working hours – quants are not obliged to be in the office for London market open for example.
On a daily basis, as a Quant Research Manager I spend the largest portion of my time on my own research projects, followed by talking to my team members about their research projects, liaising with developer teams, reading research articles, speaking to data vendors and undertaking recruitment activities.
We have no dress code, a good culture of people having lunch together, end of month company drinks, a Christmas party, an annual summer party with partners, and annual weekend away (in 2017 we went to Budapest). There are a number of company-wide clubs – running, basketball, board games, music are all popular.
For quants we have internal quant seminars on topics of general interest, an annual quant away day (talks and team building activities), and external seminars on Data Science and Machine Learning sponsored by GR at the Alan Turing Institute. There is also Biannual GR lecture from a big-ticket speaker in areas of interest: to date we’ve had speakers on quantum computing, data visualisation & AI. Our next talk is going to be given by Michael Jordan, Professor at the University of California, Berkeley.
Would I like working at G-Research?
Previously I’ve worked as both an academic and as a front office derivatives quant in an investment bank. Quant work is similar to academia, in that we work on interesting research projects with a large amount of freedom as to the direction of the project.
The thing that I miss most about academia is teaching – when I was lucky enough to have a class of bright and motivated undergraduates then I really enjoyed this. My work now also differs from academia in that typically I will look at a data set for some amount of time, and make observations on it with certain levels of confidence – Whereas working as a pure mathematician I had either proved a theorem, or I had not.
However at the end of the day the success of the business is driven by the success of quant research – a quant needs to be able to identify failing projects early. Personally I like the challenge and the urgency of this.
Is it a good place for women?
It’s a fact that women are under-represented in finance and technology companies in general, and quant roles are no exception to this. Nevertheless, I believe that working at G-Research can be a better opportunity for women than academia.
I find the working environment here much more social, collaborative and less political than working in a bank. The nature of our work means that there is continual and rapid feedback on projects, and the measures for success of a project are more concrete than your perceived reputation based on what journals you publish in.
G-Research is actively working to improve the culture and make it more inclusive. Some of the recent policies the company has implemented include:
- Enhanced Maternity leave – which offers six months full pay plus six months statutory pay
- Flextime within Quantitative Research
- Emergency childcare
As a company, G-Research acknowledges that there is still so much more that should be done improve the culture to increase the number of female employees in an industry that is notoriously male dominated, and I will fully encourage in any way that I can.
What do quants do at G-Research?
Our quants are able to focus on research without numerous other distractions. Unlike some of our competitors, all our technology, research and resources are combined to build a single, powerful platform for producing Quant research. This means we have access to a mature, powerful research platform and portfolio of analytical tools, which materially amplifies our effectiveness.
With over 150 software engineers improving the platform and adding new capabilities, vast computational capabilities and an extensive data library, our quants have the luxury of being able to focus on research and solving mathematical problems.