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Quantitative Analyst

Quantitative analysts use maths and computer coding to understand money markets and help investors make better decisions. They spot patterns in numbers and build tools to predict how markets might move.

Quantitative Analyst

60

Finance & Accounting

AI IMPACT
AI EXPOSURE TODAY60
20-YEAR SCENARIO
NOT A FORECAST95%
THE DOOR · ENTRY DIFFICULTY TODAYC
STARTING PAY£30,000 - £40,000
NO MOATNo physical, legal or personal barrier protects this work from software.

THE DOOR: ENTRY DIFFICULTY TODAY, graded A (easy) to E (extremely hard). A Careermash rule-of-thumb index built from our AI exposure index and the job's moat class. It is not a forecast and not a count of job openings.

AI EXPOSURE TODAY is a Careermash index from 0 to 100 of how exposed this job's everyday tasks are to AI today. We estimate it by matching published research on how people use AI to this job, usually by keyword or subject area, and we lower it where the work is protected (for example by physical, personal or legal requirements). It is not a direct measurement of how much people in this job use AI.

This work is being absorbed by AI
AI exposure is high for this work and nothing structurally requires a human: no licence, no physical task, no relationship at the core. Enter as the person directing the tools, not competing with them.

The role

As a quantitative analyst, you turn piles of financial data into clear answers that help traders and investors. You use maths, statistics and coding (usually Python or R) to find patterns that might make money or spot risks. It's like solving puzzles with numbers - you need to be detail-focused and good at maths, but also be able to explain what you've found so other people understand.

Most days you'll be at your computer, pulling data, testing ideas and building models. You work with traders to understand what they need, then create tools that help them. You might look at how stocks have moved in the past to predict the future, or test whether a new trading idea would have made money. The job needs you to be careful - a small mistake in a model can cost real money - and to keep learning as markets change.

Daily responsibilities

  • Develop and implement sophisticated mathematical models to assess financial risk.
  • Analyze large datasets to identify trends and patterns that inform investment decisions.
  • Collaborate with traders and portfolio managers to optimize investment strategies.
  • Present findings and recommendations to stakeholders through detailed reports and presentations.
  • Continuously monitor market conditions and adjust models to reflect changing dynamics.
  • Utilize programming languages such as Python or R to automate data analysis processes.
  • Conduct back-testing of trading strategies to validate their effectiveness.
  • Stay updated with the latest financial regulations and economic indicators impacting the market.

Does a degree help here?

A UK degree, particularly in Mathematical Sciences or a related field, provides a robust foundation in analytical thinking and problem-solving. UK universities are renowned for their rigorous curricula and strong industry connections, giving graduates an edge in securing competitive roles in finance and analytics.