Applied AI ML Senior Associate - Machine Learning Center of Excellence - Time Series Reinforcement Learning

JPMorgan Chase & Co.
London
1 month ago
Create job alert

The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.

As an Applied AI ML Senior Associate in Machine Learning Center of Excellence, you will have the opportunity to apply sophisticated machine learning methods to complex tasks including time series analysis, reinforcement learning, causal inference, and natural language processing. You will collaborate with various teams and actively participate in our knowledge sharing community. We are looking for someone who excels in a highly collaborative environment, working together with our business, technologists and control partners to deploy solutions into production. If you have a strong passion for machine learning and enjoy investing time towards learning, researching and experimenting with new innovations in the field, this role is for you. We value solid expertise in Machine Learning and Econometrics with hands-on implementation experience, strong analytical thinking, a deep desire to learn and high motivation.


Job responsibilities

Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as time-series analysis and modelling, constrained optimization and prediction for large systems, prescriptive analytics, and decision-making in dynamical systems Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production Drive Firm wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business

Required qualifications, capabilities, and skills

PhD in a quantitative discipline, . Econometrics, Finance/Accounting, Mathematics, Computer Science, Operations Research Ability to conduct literature research in unfamiliar fields Hands-on experience and solid understanding of machine learning and deep learning methods Extensive experience with machine learning and deep learning toolkits (.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. Curious, hardworking and detail-oriented, and motivated by complex analytical problems

Preferred qualifications, capabilities, and skills

Strong background in Mathematics and Statistics and familiarity with the financial services industries; Solid knowledge in financial reports analysis; understand relationships among items in Balance Sheet, Income Statement, and Cashflow statement Ability to develop and debug production-quality code and solid experience in writing unit tests, integration tests, and regression tests; Published research in areas of Machine Learning/Deep Learning/Reinforcement Learning OR Finance/Accounting at a major conference or journal

Related Jobs

View all jobs

Data Scientist - (Senior AI/ML Engineer)

Data Scientist - (Senior AI/ML Engineer)

Senior Applied Scientist - Computer Vision

Senior Applied Scientist - Computer Vision

Data Scientist | London | AI-Powered SaaS Company

Data Scientist

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.

AI Summit London 2025: A Complete Guide for UK AI Engineers & Recruiters

Artificial intelligence may be a border-less technology, but every ecosystem needs a beating heart where the community meets face-to-face. For the British Isles that heart is The AI Summit London, the headline AI event of London Tech Week, returning to Tobacco Dock on 11–12 June 2025. With eight content stages, 4 500+ attendees and 300 speakers spanning government, FTSE-100 giants and rocket-ship start-ups, the Summit offers a year’s worth of insight, deal-making and career acceleration in just 48 hours. Whether you are an AI engineer optimising vector databases, a data scientist pivoting into prompt ops, or a hiring manager scouring the market for talent, this handbook distils everything you need to hit the ground running—from ticket tactics and agenda highlights to networking hacks and post-event ROI.

AI Engineer World’s Fair 2025: The Complete UK Guide to June’s Unmissable AI Engineering Event

If 2024 was the year every product team rushed to bolt an LLM onto their roadmap, 2025 is when the craft of AI engineering finally takes centre stage. From rapid-fire prompt iterations to robust eval pipelines, the discipline now demands the same rigour we once reserved for cloud infra or mobile apps. That is precisely why the AI Engineer World’s Fair, 3–5 June 2025 in San Francisco, matters more than any keynote or press release: it is the one place where the movers, makers and maintainers of production-grade AI swap battle-tested patterns in person. For UK technologists—and the recruiters who hire them—the Fair offers a rare chance to compress a year’s worth of learning, networking and tooling discovery into three intense days. Whether you are scaling RAG systems on Azure, bootstrapping an agentic start-up from your kitchen table, or simply hunting for your first AI engineer job, the sessions, workshops and hallway conversations can tilt your career trajectory. The guide that follows distils everything you need to know—programme highlights, travel hacks, ticket tips and post-event ROI—so you can decide if a flight across the Atlantic (or a virtual pass) is the smartest investment you’ll make this year.

How to Advertise AI Jobs and List AI Vacancies: Advanced Recruitment Strategies for 2025

In a landscape where artificial intelligence (AI) is rapidly transforming industries—from healthcare and finance to manufacturing and creative fields—employers are in stiff competition to secure the best AI talent. Whether you’re a start-up looking for your first machine learning engineer or a global enterprise planning an AI research lab, knowing how to advertise AI jobs effectively has never been more critical. Below, you’ll find in-depth strategies for crafting compelling AI job adverts, optimising your recruitment funnel, and showcasing your organisation as an employer of choice for top AI specialists. We’ll also explore the importance of salary transparency, the best channels for promoting your AI vacancies, and advanced techniques for nurturing a culture of innovation.