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

Apply Now

Quantitative Research - Credit - Vice President

J.P. MORGAN
City of London
2 weeks ago
Create job alert
J.P. Morgan Global Credit Trading

J.P. Morgan Global Credit Trading delivers premier, integrated financial services to a global clientele, offering financial assets and liquidity solutions for banks, insurance companies, finance companies, mutual funds, and hedge funds. Our traders, salespeople, and research analysts collaborate to generate innovative ideas and maintain our competitive edge in the market. The Credit business facilitates secondary markets in high-grade bonds/CDS, high-yield bonds/CDS, distressed bonds, leveraged finance, indices, options, correlation products, and other exotic structures.


The Credit QR team is responsible for developing and maintaining models for pricing, risk, and P&L calculations, tooling pre-trade analytics for trading as well as refining quoting and market-making algorithms for a wide range of credit products. Alongside with hand-in-hand quantitative R&D with business stakeholders based on market themes, our responsibilities also encompass the entire model lifecycle, from new model specification, implementing models in various libraries and downstream systems, and going through review process to ensuring compliance with internal policies and industry regulations.


Job summary

As a Vice President of Quantitative Research Credit team, your primary focus will be on driving and accelerating agenda of pricing model development, prototyping and delivering analytics to business stakeholders in Macro Credit space with agility and commercial acumen. This role involves high level of engagement with sales and trading with ownership and accountability of pre-trade tools, model output and PNL analysis. Product coverage includes wide range of flow credit derivatives with a mixture between linear (Credit Index, CDS) and non-linear (Index Options, and Index Tranches) with particular emphasis on non-linear products.


Job responsibilities

  • Prototype and deliver pre-trade quantitative analytics upon market volatility, trading opportunity as well as client wallet, particularly for index options and tranches.
  • Modernize trading & risk systems with technology partners to achieve high performance and robust risk & PNL attribution while accelerating decommissioning of legacy analytical system.
  • Enhance pricing models to facilitate comprehensive scenario pricing and default analysis.
  • Collaborate with trading with ongoing brainstorming and agile R&D given market themes.
  • Drive the automation agenda by transforming manual processes into digital platforms.
  • Write technical model documentation compliant with internal and regulatory standards and engage with model control teams to facilitate timely and efficient reviews and approvals.

Required qualifications, Capabilities, and skills

  • 3-7 years of experience as quantitative researcher / strategist in credit and fixed income business with outstanding analytical skills and structured approach to problem-solving.
  • Advanced degree in math, statistics, physics, financial engineering, or computer science.
  • Strong knowledge in financial mathematics, stochastic calculus (volatility model and correlation model as a big plus).
  • Proficient in python or C++ with familiarity to collaborative software development process in a dynamic and demanding environment.
  • Team-work mentality with excellent oral and written communication skills with business stakeholders, technology partners and control functions.
  • Ability to work effectively in a high-pressure environment with result-driven mentality and attention to details.

Preferred qualifications, capabilities, and skills

  • Experience with Neutral Networks (or alternative machine learning / deep learning models), or Large Language Model tuning.

J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.


#J-18808-Ljbffr

Related Jobs

View all jobs

Quantitative Researcher, Reporting & Insights (SRE/RM Level)

Quantitative Researcher (Equity)

Quantitative Researcher / PM | Mid-Freq Equities

Quantitative Researcher / PM | Mid-Freq Equities

Quantitative Researcher

Quantitative Researcher (Machine Learning)

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.

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.

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.

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.