Quant Research

1What you'd actually do

• Cleaning and organising large datasets - market prices, trade records, company fundamentals, or 'alternative data' such as satellite imagery or web traffic - and checking for errors, survivorship bias and gaps before anything can be modelled
• Writing code, most often Python and sometimes C++, to test whether a hypothesis about market behaviour actually holds historically (this is called 'backtesting')
• Running statistical analysis on results and trying hard to break your own findings - checking whether a signal survives transaction costs, works out of sample, or is just an artefact of overfitting to past data
• Reading research: academic papers, internal notes from colleagues, or documentation on a new instrument or exchange rule change
• Talking with traders or portfolio managers about what the model is doing, why it lost money last week, and whether a real-world constraint (liquidity, borrow costs, position limits) has been captured
• Maintaining and monitoring models already in production - checking they still behave as expected, investigating anomalies, and re-fitting or retiring them when markets shift
• In derivatives-pricing quant work specifically: deriving or implementing pricing models, calibrating them to observable market prices, and writing up the maths so others can validate it

2How graduates get in

• Direct graduate hire from a quantitative degree - this is the most common route. Hedge funds, proprietary trading firms and bank quant teams recruit small numbers of graduates directly, often with recruitment starting very early in the final year or even earlier.
• A summer internship the year before, which for many trading firms and funds is the main pipeline into graduate roles - converting an internship is a far more reliable route than applying cold.
• PhD entry. In many quant research teams, particularly at hedge funds and in bank derivatives modelling, a PhD in maths, physics, statistics, computer science or a related field is normal rather than exceptional. Some teams hire almost exclusively at PhD level.
• A specialist master's - MSc in Financial Mathematics, Financial Engineering, Statistics, Computational Finance or similar. Common for bank pricing/risk quant roles and useful if your undergraduate degree was quantitative but you have no finance exposure.
• Sideways from an adjacent quant role - starting in quantitative risk, model validation, quant development or quant analytics at a bank and moving into research later. Slower, but a genuine route, especially for people who did not get into a front-office team straight out of university.
• From outside finance entirely - some people move in from academic research, machine learning roles in tech, or data science, particularly where the firm cares more about research ability than finance knowledge. Less structured and usually not a graduate-level entry point.

3What employers ask for

• A strongly quantitative degree: maths, statistics, physics, computer science, engineering, or economics with heavy mathematical content. The subject genuinely matters here in a way it does not for most graduate jobs - a non-quantitative degree is a serious obstacle.
• High grades. A first or high 2:1 is the usual expectation, and many quant employers also look at A-level results (particularly Maths and Further Maths) even for graduates and PhD applicants.
• Programming ability, usually Python. Some firms also want C++ for lower-latency work. You are typically tested on this rather than taken at your word.
• Solid grasp of probability, statistics and linear algebra - not just having passed the modules, but being able to reason with them under pressure in an interview.
• Whether a PhD is required varies enormously. Some hedge funds and bank modelling teams treat it as effectively necessary; many proprietary trading firms hire strong undergraduates straight out. Check individual job adverts rather than assuming.
• Prior finance knowledge is often not required, especially at trading firms - several deliberately prefer to teach it. Bank pricing-quant roles are more likely to expect familiarity with derivatives and stochastic calculus.

4Skills that matter

5Where it leads

1. Junior/graduate quant researcher, typically working on well-defined pieces of a larger research problem set by someone senior, with your work heavily reviewed. How long this lasts varies a lot - at some firms a year or two, at others longer.

2. Quant researcher with ownership of your own strategies or models. You choose what to investigate, and your work goes into production with your name attached to its performance.

3. Senior quant researcher or team lead - setting research direction, mentoring juniors, and taking responsibility for a book of models or a whole signal area. Timelines here vary enormously and depend far more on results than on years served.

4. From there the paths diverge: some move towards portfolio manager or trader roles where they run capital directly; some move into head-of-research or head-of-quant positions managing large teams; some specialise deeply and stay technical.

5. Exits are common too - into quantitative roles in tech and machine learning, into founding or joining a small fund, or into quant risk and model validation, which is generally less pressured and more predictable.

6Where this varies

"Quant research" covers quite different jobs depending on where you work. At hedge funds and proprietary trading firms it is mainly statistical research on data to find trading signals, close to the money, with performance judged on whether your ideas make money. At investment banks it more often means derivatives pricing and modelling - deriving and implementing models to value and hedge complex products, with more emphasis on stochastic calculus and on documentation for regulators. There is also a large quantitative risk and model validation world, which checks and challenges other people's models, is generally more process-driven and regulated, and typically pays less but with more predictable hours. Geographically, the UK market is overwhelmingly concentrated in London, with some quant work in Edinburgh, and asset-management-flavoured roles more spread out than trading roles. Hours also vary: bank quant roles are often reasonably contained, whereas some trading firms and funds expect longer and more intense weeks.