Junior Quantitative Analyst

Marex
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist - Game Analytics

Data Science Manager

Data Science Manager

Data Science Manager

Sr. Data Scientist

Senior Sports Data Scientist

Marex is a diversified global financial services platform, providing essential liquidity, market access and infrastructure services to clients in the energy, commodities and financial markets.

The Group provides comprehensive breadth and depth of coverage across four core services: Market Making, Clearing, Hedging and Investment Solutions and Agency and Execution. It has a leading franchise in many major metals, energy and agricultural products, executing around 50 million trades and clearing 205 million contracts in 2022. The Group provides access to the world's major commodity markets, covering a broad range of clients that include some of the largest commodity producers, consumers and traders, banks, hedge funds and asset managers.

Marex was established in 2005 but through its subsidiaries can trace its roots in the commodity markets back almost 100 years. Headquartered in London with 36 offices worldwide, the Group has over 1,800 employees across Europe, Asia and America.

For more information visit www.marex.com

The Quantitative Analyst will continuously be challenged around model risk management, model validation, pricing methodology and quantitative model development of various pricing and risk engines. They will gain exposure to various asset classes with a strong appreciation for the complexities across the various commodity and equity markets. Development of independent coding libraries and routines is required.

Responsibilities:

•Contribute to the Model Risk Management framework for Structured Financial products and exotic trades.
•Contribute to independent model validation of Front Office Analytics libraries and models for equities, FX, Credit and commodities.
•Produced high quality quantitative analysis and model validation documentation (LaTeX).
•Enhancement of the risk management infrastructure through the transformation of data with coding.
•Ongoing model development for valuation and risk measurement, carrying out reviews and calibration of model parameters to help ensure best practice is followed.
•Develop and implement tactical & strategic risk tools to provide analysis and potential reporting capabilities to the overall team.
•Build & maintain historic data sets across price and implied volatility surfaces to support pricing and risk models.
•Quantitatively analyse new product structures and identify embedded risks using Monte Carlo simulation-based modelling and other methods.
•Maintain and extend a Stress Portfolio Options Engine used for margining calculations.

Skills and Experience:

Essential
•Strong quantitative and analytical skills, including Stochastic Calculus, Stochastic Processes, Numerical Analysis, Derivative Pricing, Computational Finance and Quantitative Risk Management.
•Excellent programming knowledge using object oriented programming with various programming languages (Python, C++, C#, etc.)
•Professional in creating well-structured documents using scientific typesetting software i.e. LateX, Lyx, Beamer etc.
•Experience in assessing, quantifying and implementing appropriate portfolio price and stress tests.
•Master's degree/PhD in Maths, Physics, Engineering, Quantitative Finance, Computer Science or any related field (or equivalent qualification or experience).
•High-quality assessment of a wide range of potential complex transactions, carrying out modelling and analysis as necessary, advising upon the value and risk-related quantitative issues associated with the proposals.
•Some familiarity in volatility surface construction and calibration.

Desirable
•Relevant exotic options work experience including knowledge of commodities.
•Structured Products and Hybrid structures.
•Options or/and Volatility trading.
•Machine Learning related to Finance techniques.
•IT and Software Development oriented mentality.

If you're forging a career in this area and are looking for your next step, get in touch!

Marex is fully committed to being an inclusive employer and providing an inclusive and accessible recruitment process for all. We will provide reasonable adjustments to remove any disadvantage to you being considered for this role. We value the differences that a diverse workforce brings to the company.  We welcome applications from candidates returning to the workforce.  Also, Marex is committed to avoiding circumstances in which the appearance or possibility of conflicts of interest may exist within the hiring process.

If you would like to receive any information in a different way or would like us to do anything differently to help you, please include it in your application.


#LI-MH1

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.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

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

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.