Quantitative Research

Quantitative researchers ("quants") use maths, statistics and programming to find patterns in financial market data and turn them into trading strategies or pricing models. Most work at hedge funds, proprietary trading firms, asset managers or investment banks, building and testing models that decide what to buy and sell, or that value complex financial products like derivatives. The same job title also exists outside finance — in market research and social research agencies it means designing and analysing surveys and large datasets — so always check which type of quantitative research an advert means.

Starting salary: £60k–£100k
Live graduate jobs: 14 open now
Main way in: Direct application to a hedge fund or proprietary trading…
They usually ask for: A strongly quantitative degree

Approximate graduate salary

In finance, starting packages are typically somewhere around £60,000–£100,000 or more including bonus, though this varies enormously by firm type — proprietary trading firms and leading hedge funds sit well above bank quant teams, and PhD hires usually start higher than bachelor's hires. Outside finance, quantitative research roles in market research, social research or policy analysis typically start far lower, often broadly in the £25,000–£35,000 range. All of these are rough approximations and depend heavily on employer, location and whether bonus is included.

What you'd actually do

Cleaning and wrangling large datasets — price histories, order book data, company fundamentals, sometimes 'alternative data' like satellite imagery or web-scraped prices — and checking it for errors, gaps and survivorship bias before it can be trusted
Writing code, usually Python, sometimes C++, R or kdb+/q, to test whether a trading idea would have made money historically (a 'backtest') and whether that result survives transaction costs and realistic assumptions
Running statistical tests to work out whether an apparent pattern is a genuine signal or just noise you've fitted to by looking at the data too many times
Reading academic papers, internal research notes and market commentary, then trying to reproduce or adapt an idea on your firm's own data

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Presenting findings to a portfolio manager, trader or senior researcher — usually a short, blunt conversation about whether the result is real and what could break it
Monitoring strategies or models already running in production, investigating when live performance drifts away from what the research predicted
In a bank's quant team specifically: deriving or implementing pricing and risk models for derivatives, documenting them, and dealing with model validation and regulatory review

How graduates get in

Direct application to a hedge fund or proprietary trading firm's graduate or intern programme — the most common route into buy-side quant research. These tend to recruit small numbers, very early in the academic year, and test heavily on maths, probability and coding
Investment bank graduate schemes with a dedicated quantitative stream (often called quantitative analytics, quant strats or model risk). More structured, larger intake, and more likely to take people without a PhD
Direct PhD hire — very common in this field, unlike most graduate careers. Maths, physics, statistics, computer science and econometrics PhDs are routinely recruited straight into research roles, sometimes at a higher starting level than master's graduates
A specialist master's such as an MSc in Financial Mathematics, Mathematical Finance, Statistics, Computational Finance or Machine Learning — a well-trodden route, particularly for people whose undergraduate degree was strong but not quantitative enough

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Moving sideways from an adjacent role — quant developer, data scientist, risk analyst or trading technology — after building a track record. Common, but usually takes a few years
Maths and programming competitions, open-source projects or published research can get you noticed directly; some firms care more about demonstrable problem-solving than where you worked

What employers ask for

A strongly quantitative degree — maths, statistics, physics, engineering, computer science, or economics with heavy econometrics. The subject genuinely matters here, more than in almost any other graduate field; a non-quantitative degree is a serious obstacle without a conversion master's
Typically a first or high 2:1, and often strong A-levels including Further Maths. Some firms ask about A-level or admissions-test results even years later, which is unusual but normal in this corner of the market
A master's or PhD is expected at many buy-side firms and is common though not universal at banks. This varies a lot — some proprietary trading firms happily hire straight from a bachelor's if you perform well in their tests
Real programming ability, usually Python plus familiarity with something lower-level like C++. You will be asked to write working code, not just talk about it

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Comfort with probability, linear algebra, statistics and (for derivatives roles) stochastic calculus. Interviews commonly include mental maths, probability puzzles and estimation questions
No mandatory professional qualification. The CFA or the Certificate in Quantitative Finance exist and some people take them, but neither is a gatekeeper the way the actuarial or accountancy exams are in their fields

Skills that matter

Statistical scepticism

Most promising-looking results are overfitting or data errors, and the researcher's main value is spotting that before the firm risks money on it.

Programming for data, not just algorithms

A large share of the week is spent loading, joining, cleaning and reshaping messy datasets, so fluency with data tooling matters more than elegant computer-science solutions.

Probability and stochastic reasoning

It underpins both derivatives pricing and the judgement of how much of a strategy's past return was luck.

Explaining a model to someone who won't read the maths

Traders, portfolio managers and risk committees decide whether your work gets used, and they need the intuition and the failure modes in a few sentences.

Research discipline and record-keeping

You need to be able to say exactly what data, parameters and assumptions produced a result months later, because someone will eventually ask why live performance differs.

Tolerance for negative results

Most ideas tested do not work, and people who need a positive outcome to feel productive tend to talk themselves into bad ones.

Putting these on a CV? We counted which skills 12,914 live graduate adverts ask for, and what to do with the answer — part of our application advice.

Where it leads

Junior or graduate quantitative researcher — working on well-defined pieces of a larger project, usually under a senior researcher who sets the question. Expect a significant period before you own a strategy or model outright.
Quantitative researcher with ownership of a signal, strategy or model — you choose the research direction, and your work is judged on whether it makes money or survives validation.
Senior researcher or team lead, supervising juniors, setting the research agenda and allocating effort across ideas. Timelines here vary enormously — at small firms this can come quickly, at large banks it is slower and more structured.
Branching point: some move into portfolio management and take direct responsibility for risk and returns; others stay technical as a principal researcher; others move into quant development, model risk management, or data science outside finance.
Longer term, partner or head-of-research roles at a fund, or launching a fund. A smaller but real path is leaving for technology or academia, where the coding and statistics transfer readily.

What people get wrong

“It's a trading job — you'll be watching screens and making calls on the market.”

Most quantitative researchers rarely place a trade. The work looks far more like computational science: writing code, running experiments, arguing about methodology. Execution is usually someone else's job or fully automated.

“You need to know a lot about finance and markets to get hired.”

Many firms prefer to hire raw mathematical and coding ability and teach the finance, because finance knowledge is learnable in months and research instinct isn't. Turning up with strong puzzle and coding performance but patchy market knowledge is normal.

“A PhD is a nice-to-have, as in most graduate careers.”

In buy-side quant research a PhD is often the default rather than the exception, and some teams are composed almost entirely of doctorates. This is one of the few UK graduate fields where postgraduate study genuinely changes which doors open.

“Success means building clever models.”

Much of the value comes from unglamorous data work and from killing ideas that look good but aren't. A researcher who correctly rejects most of their own work is doing the job properly.

Where this varies

The title covers quite different jobs. At hedge funds and proprietary trading firms, quantitative research means hunting for trading signals, and the culture is small-team, performance-measured and often secretive. At investment banks, it more often means derivatives pricing, risk modelling and model validation — more mathematically formal, more regulated, more documentation, and more structured graduate training. In asset management it sits between the two, with longer horizons and more emphasis on portfolio construction. Entirely separately, market research and social research agencies, polling organisations, government analytical services and universities also advertise "quantitative research" roles, which mean survey design, sampling and statistical analysis of social data — a lower-paid, differently-skilled field that shares the statistics but not the finance. Geographically, finance quant roles cluster heavily in London, with smaller pockets elsewhere; non-finance quantitative research is spread much more widely across the UK.

See all 14 live Quantitative Research jobsFrom employers' own careers sites, updated daily Tailor your CV for this roleFree with an account, 3 a month

General guidance about the role across the UK market, not about any specific employer. Entry routes and requirements vary — always check the individual job advert.