Quantitative Strategist

Anson McCade
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Machine Learning Engineer

Data Scientist

Machine Learning Engineer (Manager)

Machine Learning Engineer

About the Company

My Client is a leading Marco Hedge Fund looking to hire experienced pricing quants at their office in London. The firm has a collaborative environment where team leaders have access to a wealth of internal resources. This is an opportunity to work with highly diverse and intelligent colleagues, in a top performing Hedge fund.



About the Role

The Investment Quant (IQ) team is responsible for development and maintenance of pricing models, trading tools, risk management tools, and relative value opportunity identification tools. IQ team members are also the first line of support to the business when it comes to all the derivatives pricing and risk tools.



Qualifications

  • A Levels at grade A*/A and a 1st class degree with MA or PhD in a numerate field from a Russell Group
  • University (or equivalent international secondary/tertiary education)
  • EITHER 4-5+ years of non-linear/vol experience on a trading desk for a tier 1 bank, or buy side firm, OR 4-5+ years working as Quant but with strong software development skills
  • Excellent maths intuition
  • An intuitive understanding of derivatives and market knowledge
  • Experience in data analysis using Python based tools
  • Minimum 4 years’ experience in object-oriented programming in an enterprise-level code base, ideally one of C#, C++ or JAVA
  • Minimum 4 years’ experience of Pricing and Modelling
  • Knowledge of Machine Learning
  • Ability to pick up new skills quickly and thrive in fast-paced environments
  • Good communication skills and a pragmatic problem solver
  • Ability to work independently and with initiative
  • Ability and drive to work in a collaborative team environment



Required Skills

  • Rates quant with strong mathematical and programming skills
  • Experience in building cutting edge Rates trading tools and other analytics



Preferred Skills

  • Experience in data analysis using Python based tools
  • Knowledge of Machine Learning

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers Jobs

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Education Jobs

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.