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

Apply Now

Quantitative Developer

Reed Talent Solutions
London
1 week ago
Create job alert

A global investment bank is seeking a highly skilled and motivated Quantitative Analyst to join the XVACCR, Collateral & Credit Quantitative Research team. This role is central to the development of cutting-edge quantitative models and tools that support XVA pricing, counterparty credit risk, collateral management, and regulatory compliance.


You will work closely with desks across the bank including XVA, Risk, Collateral, and Credit Trading, contributing to strategic initiatives and regulatory projects such as XVAVaR, SACCR, FRTB-CVA, and RWA optimisation. This is a unique opportunity to be part of a dynamic team driving innovation in financial modelling and quantitative research.

This is a permanent role based in the City of London office (hybrid working - 3 days per week onsite).


Key Responsibilities

  • Develop and implement pricing models and analytical tools for:
  • Collateral Management (e.g., IMVA-CCP, SIMM)
  • XVA-related activities (e.g., CVA, DVA, FVA, MVA)
  • Collaborate with internal stakeholders including Trading, Risk, RPC, and IT to ensure model accuracy and performance.
  • Contribute to the enhancement of XVA libraries and platforms to meet evolving regulatory requirements.
  • Support the development of the Collateral Management platform for CCP and EMIR Initial Margin.
  • Participate in system migration projects and optimisation initiatives using advanced modelling techniques (e.g., AAD, Machine Learning).


Candidate Profile

Essential Skills & Experience:

  • Strong programming skills in C++.
  • Solid understanding of numerical methods such as Monte Carlo simulations and optimisation algorithms.
  • Experience with:
  • Distributed computing and inter-process communication
  • Multi-threading programming
  • Microsoft Office, VC++, VBA
  • SQL databases (Access, Oracle)
  • Web technologies (XML, XSLT)
  • Proven ability to work independently and as part of a team.
  • Excellent analytical and problem-solving skills.
  • Strong communication skills, both written and verbal.
  • Creative and results-oriented with a proactive approach to learning and adapting.

Related Jobs

View all jobs

Quantitative Developer (Python) - Hybrid London - Up To 250k

Quantitative Developer

Quantitative Developer

Quantitative Developer

Quantitative Developer

Quantitative Developer

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.

Jobs

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

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Jobs

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Jobs

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

🍪 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.