2026 Machine Learning Center of Excellence Summer Associate - Time Series & Reinforcement Learning Internship - (6 months)

Descripción del puesto:

The Machine Learning Center of Excellence (MLCOE) is a world-class machine learning team which continually advances state-of-the-art methods to solve a wide range of real-world financial problems using the company's vast and unique datasets.
As a 2026 Machine Learning Center of Excellence Summer Associate within our dynamic team, you will be given the chance to utilize advanced machine learning techniques across a range of intricate domains such as finance, banking, economics, marketing, natural language processing, reinforcement learning, accounting, operations management,
Job responsibilities:
* Create strategically important AI/ML application in the Chief Data & Analytics office. Our work spans across all of J.P. Morgan's lines of business including Commercial & Investment Bank, Asset Wealth Management, Consumer & Community Banking, and through every part of the organization from front office sales and trading to operations, technology, finance and more.
* Embrace opportunity to explore novel and complex challenges that could profoundly transform how the firm operates.
* Collaborate closely with our MLCOE mentors, business professionals, and technologists, carrying out independent research and providing solutions to the business.
* Demonstrate deep passion for machine learning, robust expertise in deep learning with practical implementation experience, and a dedication to learning, researching, and experimenting with innovations in the field.
Required qualifications, capabilities and skills
* Enrolled in or completed a PhD in a quantitative discipline, e.g., Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, Data Science, or related fields, or equivalent research or industry experience. We especially welcome post-doctoral students, or people interested in a change of career as well.
* Strong background in Programming, Mathematics and Statistics.
* Published research in areas of machine learning, science, engineering, quantitative psychology, or business related areas.
* Expected PhD graduation date of December 2026 through August 2027 or already graduated.
* Familiarity with state-of-the-art practice in these domains or knowledge such as Finance, Economics, Accounting, Marketing, Operation Research.
* Good background in various fields of mathematics and statistics, such as Stochastic Calculus, Bayesian techniques, Statistics, State-Space models, MCMC, MCTS
* Knowledge and experience with Machine Learning and Reinforcement Learning methods.
* Proficient in Python, and experience with machine learning and deep learning toolkits such as TensorFlow, TensorFlow Probability and Jax.
* Scientific thinking, ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals.
* Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
* Ability to develop and debug production-quality code.
* Familiarity with continuous integration models and unit test development.
* Familiarity with the financial services industries
* Innovative problem-solvers with a passion for developing solutions that support our global business.
* Curious, hardworking, detail-oriented and motivated by complex analytical problems.
* Ability to work both independently and in highly collaborative team environment
* CFA, ACCA, or any other finance and accounting qualifications
* PCAP or any other programming or software engineering qualifications. Do mention any Coursera or other online certificates in your CV