Junior Quantitative Analyst

Marex Spectron
London
11 months ago
Applications closed

Related Jobs

View all jobs

Junior Data Analyst

Junior Data Analyst

Junior Data Analyst

Junior Data Analyst - Verisure

Junior Data Analyst - Studentjob.co.uk

Staff Data Analyst

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 visitwww.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:

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

Skills and Experience:

Essential

  1. Strong quantitative and analytical skills, including Stochastic Calculus, Stochastic Processes, Numerical Analysis, Derivative Pricing, Computational Finance and Quantitative Risk Management.
  2. Excellent programming knowledge using object oriented programming with various programming languages (Python, C++, C#, etc.)
  3. Professional in creating well-structured documents using scientific typesetting software i.e. LaTeX, Lyx, Beamer etc.
  4. Experience in assessing, quantifying and implementing appropriate portfolio price and stress tests.
  5. Master’s degree/PhD in Maths, Physics, Engineering, Quantitative Finance, Computer Science or any related field (or equivalent qualification or experience).
  6. 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.
  7. Some familiarity in volatility surface construction and calibration.

Desirable

  1. Relevant exotic options work experience including knowledge of commodities.
  2. Structured Products and Hybrid structures.
  3. Options or/and Volatility trading.
  4. Machine Learning related to Finance techniques.
  5. 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.

#J-18808-Ljbffr

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.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.