Junior Quantitative Analyst

Marex Spectron
London
2 months ago
Applications closed

Related Jobs

View all jobs

Data Science Manager – Gen/AI & ML Projects - Bristol

Quantitative Researcher (Machine Learning)

Senior Data Scientist – Machine Learning -  Defence –Eligible for SC

Senior Data Science Consultant – Econometrics specialist

Deep Learning Researcher – HFT Prop-Firm

Junior 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

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.