Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Quant Developer

Experis
London
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Machine Learning Quant Engineer - Investment banking

Machine Learning Quant Researcher

Senior Quant/Risk Professional - Machine Learning, Surveillance

Senior Quant/Risk Professional - Machine Learning, Surveillance

Senior Quant/Risk Professional - Machine Learning, Surveillance

Location: London Job Type: Contract Industry: Cloud & Infrastructure Job reference: BBBH384924_1731406913 Posted: about 2 hours ago

Job Title: Quantitative Developer
Duration: Six Months (with potential for extension)
Location: London (Hybrid Work Model)

Role Overview

Our Equity Derivatives Quant team within Global Banking and Markets is seeking a skilled C++/Python Quant Developer with a strong background in Structured Equity Derivatives. This role will focus on enhancing and maintaining our pricing, risk, and P&L infrastructure to support a high-performance trading platform.

Key Responsibilities

Pricing and Risk Infrastructure: Collaborate in designing and implementing infrastructure for pricing, risk management, and P&L functionalities that support the core pricing library. Quantitative Library Development: Work alongside Quantitative Modellers to evolve and optimize the core pricing library. Tooling and Platform Support: Build and maintain quantitative tools necessary for supporting the platform's operational and analytical needs.

Project Focus Areas

FRTB IMA Regulatory Reporting: Develop calculation infrastructure to meet Fundamental Review of the Trading Book (FRTB) internal model approach (IMA) regulatory standards. Risk and P&L Calculations: Design and implement end-of-day and intraday risk/P&L calculations, enabling the phase-out of legacy platforms. Market Data Pipelines: Create automated data marking pipelines for market data processing and integration.

Collaboration and Interaction

The successful candidate will engage closely with trading desks, other quantitative analysts, Risk and Finance teams, and broader technology teams. While based in London, the role involves coordination with teams and clients across London, Paris, Hong Kong, and Bangalore, and may require occasional travel.

Requirements

Essential Qualifications and Skills

Experience: 3-7 years in a quantitative finance, IT development, or trading environment, ideally as a Quantitative Analyst. Educational Background: Bachelor's or Master's degree in mathematical finance, mathematics, science, or related field from a top-tier university. Technical Proficiency: C++: Minimum 2 years (experience with Visual Studio 2017 preferred)Python: Minimum 2 years Domain Knowledge: Understanding of standard pricing models used in the investment banking sector.

Preferred Skills and Knowledge

Quantitative Expertise: Knowledge in stochastic processes, probability, and numerical analysis; backgrounds in physics, engineering, or similar disciplines are advantageous. Data and Instrument Knowledge: Experience with data analysis and familiarity with primary equity and equity derivatives instruments.Knowledge of instrument pricing, sensitivity analysis, P&L prediction and explanation, and risk measures like VaR and Expected Shortfall (ES). Technical Skill Set: Experience with distributed computing and data serialization. Proficiency in Excel and experience with CI/CD pipeline tools. Soft Skills: Ability to thrive in a fast-paced environment and manage multiple priorities efficiently.

This role offers the opportunity to contribute to a globally integrated team, engage in impactful projects, and support cutting-edge trading and risk management systems.

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.