Senior Machine Learning Engineer (VP) - Intelligent Solutions
JPMorgan Chase Intelligent Solutions (JPMIS) is a new group considering ways to transform our data assets into opportunities for JPMorgan Chase by leveraging the vast amount of proprietary data across the firm. Protecting and managing intellectual property effectively as well as utilizing it to develop solutions that are both customized and scalable will enable the firm to create value for our shareholders.
The Machine Learning team at JPMorgan Chase combines cutting edge machine learning techniques with the company’s unique data assets to optimize all the business decisions we make. In this role, you will be part of our world-class machine learning team, and advance the state-of-the-art in financial applications ranging from pricing and credit models to natural language processing. Our work spans the company’s lines of business, with exceptional opportunities in each.
The successful candidate will develop new machine learning methods tailored to banking applications such as risk assessment, trading models, customer relationship management, and pricing models. Machine learning techniques will include feed-forward, recurrent, recursive and convolutional neural networks, maximum entropy models, and other algorithms related to time series analysis and supervised learning. In addition to using and adapting existing models, you will be expected to develop new techniques especially suited to banking applications. The candidate will help in the identification and solution of new problem areas.
- Expertise in linear algebra and calculus is required.
- Familiarity with toolkits such as Torch, Theano, TensorFlow, Chainer and others is desirable.
- A bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, Statistics or related field is required. (Graduate degree or PhD. preferred) and 5+ years of relevant experience is required.