JPMorgan Machine Learning Center Excellence Summer 

United Kingdom, England, London 

284672766

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 predictions, market modelling, and decision optimizations.
• Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production

Required qualifications, capabilities, and skills

• Ph.D. or in the last year of a Ph.D. program in machine learning, statistics, mathematics, computer science, economics, finance, science, engineering, or other quantitative fields
• Knowledge of machine learning / data science theory, techniques, and tools
• Scientific thinking, ability to work with literature and the ability to implement complex projects
• Ability to understand business problem, study literature for a solution approach, write high quality code for the chosen method, design training and experimentation to validate the algorithms and implementation, and to 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 work both independently and in highly collaborative team environments
• Excellent analytical, quantitative, and problem-solving skills and demonstrated research ability
• Curious, hardworking, detail-oriented and motivated by complex analytical problems

Preferred qualifications, capabilities, and skills

• Knowledge of Financial Mathematics, Stochastic Calculus, Bayesian techniques, Statistics, State-Space models, MCMC, DSGE models, MCTS / distributedcompute, NLP, accounting
• Knowledge and experience with Reinforcement Learning methods
• Knowledge of python, Tensorflow, tf-agent, Ray, RLLib, Tune, or other ML frameworks, etc.
• Experience with any of OOP, graph-based computation engines, large scale software development, C++/Java/CUDA, performance focused implementations, numerical algorithms, distributed computing, cloud computing, data transformation pipelines
• Familiarity with continuous integration models and unit test development
• Published research in areas of natural language processing, speech recognition, reinforcement learning, or deep learning at a major conference or journal
• Strong passion for machine learning and habits to invest independent time towards learning, researching, and experimenting with innovations across a variety of fields.