2026 Machine Learning Center of Excellence Summer Associate – Time Series & Reinforcement Learning Internship – (6 months)
Chase bank
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, MCTSKnowledge 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 industriesInnovative 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 environmentCFA, ACCA, or any other finance and accounting qualificationsPCAP or any other programming or software engineering qualifications. Do mention any Coursera or other online certificates in your CV.
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