Global Credit Trading - Automated Trading Strategies - Vice President

JPMorgan Chase & Co.
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Python Data Scientist

Machine Learning Engineer, London

Machine Learning Engineer, London

Data Scientist

Machine Learning Engineer, London

DATA SCIENCE CONSULTANT BIRMINGHAM

As a Vice President in the Automated Trading Strategies team, you will be primarily focusing on Credit (corporate bonds) markets. The Automated Trading Strategies (ATS) group is responsible for systematic trading across FX, Rates, Commodities, and Credit markets, designing and implementing automated pricing, risk management and hedging, and order execution strategies. You will work closely with other internal parties (voice trading desks, sales, product, and technology) to understand the needs of clients and advance JPMorgan’s market-leading electronic services.

You must be responsible, independent, driven, and able to work in smooth collaboration with the wider team. The environment is fast-paced and challenging. The group is globally distributed so you must have clear written and verbal communication is required. You are also expected to cover a wide range of responsibilities - spanning trading, quantitative research, and technology—and some on call time will be expected.

Job Responsibilities

Analyze of data to identify patterns and revenue opportunities  Conduct back testing and assessing pricing, risk management and execution strategies Expand the group’s library of modelling, analytics, and automation tools Review trading performance and making data driven decisions Maintain and improve trading software systems and tools Resolve day-to-day trading issues

Required qualifications, capabilities, and skills

Significant experience in Quantitative Trading or similar roles. You have degree in computer science, math, physics, engineering, or other quantitative fields You have relevant full-time experience You demonstrate strong programming skills in C++/Java or other object-oriented languages You demonstrate good knowledge of statistics and machine learning You have attention to detail, adaptable, driven and collaborative You demonstrate interest in markets and systematic trading

Preferred qualifications, capabilities, and skills

Ability to understand and map data flows across applications and data sources  Prior experience in Credit or Rates markets (cash or swaps) Knowledge of order types, L2 market data, and central limit order books Experience with KDB+/q

This role encompasses the performance of UK regulated activity. The successful candidate will therefore be subject to meeting UK regulatory requirements in the assessment of fitness, propriety, knowledge and competence (as assessed by the Firm) and (where appropriate) approval by the UK Financial Conduct Authority and/or the Prudential Regulation Authority to carry out such activities.

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.

Jobs

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

Jobs Careers

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Jobs

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.

🍪 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.