Senior Lead Software Engineer - Python / Credit Technology Data

JPMorgan Chase & Co.
London
2 months ago
Applications closed

Related Jobs

View all jobs

Lead Data Engineer

High Salary: Senior Data Engineer, Consultant...

Principal MLOps Engineer - Chase UK

CDD Platform Lead

CDD Platform Lead

CDD Platform Lead

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorgan Chase within the Commercial and Investment Bank's Credit Technology team - you will lead a technical area and drive impact within teams, technologies, and projects across departments. Utilize your in-depth knowledge of software, applications, technical processes, and product management to drive multiple complex projects and initiatives, while serving as a primary decision maker for your teams and be a driver of innovation and solution delivery.

The successful candidate will focus on development of our strategic data platform and partner closely with our business stakeholders, quantitative research partners and broader technology team. The team is responsible for developing our data platform and integrating data solutions with our trading platform used across our global Credit Trading business. You will be driving development of software components for the firm’s state-of-the-art technology products in a secure, stable, and scalable way.

Job responsibilities

Develop data solutions across both real-time and end of day business needs for Credit Securities, Derivatives and Exotics products. Develop innovative software solutions to deliver scalable and reliable front office data services. Accountability for coding decisions, control obligations, and measures of success such as cost of ownership, maintainability, and portfolio operations Introduce new technologies and solutions to increase operational stability and productivity Influences peer leaders and senior stakeholders across the business, product, and technology teams Designs and develops with consideration of upstream and downstream systems and technical implications.  Learns and applies system processes, methodologies, and skills for the development of secure and stable systems.

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and 5+ years applied experience Expert applied experience in front office technology and financial data landscape Strong understanding of Python and object-oriented concepts  Experience developing or leading cross-functional teams of technologists Hands-on practical experience in system design, data engineering, application development and operational stability  Creative, quick-thinking, pragmatic, with an aptitude for solving problems with technology and an ability to quickly translate requirements into a sound technical design and implementation. Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field Understanding of Credit or similar financial markets products Experience across one or more database technologies: RDBMS (. Oracle, Postgres), Time-series Databases (. KDB+, Vertica) Experience in AWS solutions and services beneficial

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.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!

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

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

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

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.