Machine Learning Scientist - Time Series Reinforcement Learning - Vice President - Machine Learning Center of Excellence

Our Time Series & Reinforcement Learning team is a passionate group of academics and ML engineers building AI inductive reasoning systems across the firm. In leading ML science in the “Derivatives House of the Year 2022” (Risk Magazine Award), this team works closely in exploring cutting-edge research and applying the latest Machine Learning techniques to J.P. Morgan’s unique data assets. Our work spans the company’s lines of business, with exceptional opportunities in each.

As a Machine Learning Scientist in the Time Series Reinforcement Learning team, you will apply sophisticated machine learning methods to banking applications including 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.

 

You will be called upon to draw from your research and work experience to help us implement intelligent and practical algorithms at scale. The ideal candidate will have a deep understanding of the various techniques, models and cutting edge practices in machine learning and will have insight into what works best in real-world situations. You will be at the centre of prescribing, designing and building mission-critical solutions.

 

Job responsibilities

• Develop scalable tools leveraging machine learning and deep learning models to solve real-world problems for various problems related to finance, economics and operations of JP Morgan.
• Collaborate with all of JPMorgan Chase's lines of businesses, such as Investment Bank, Commercial Bank, and Asset Management.
• Lead your own project. Suggest, collect and synthesize requirements. Create an effective roadmap towards the deployment of a production-level machine learning application.

 

Required qualifications, capabilities and skills

• PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Operations Research, Data Science
• For VP position, several years of working experiences
• Experiences in machine learning project development
• Knowledge of machine learning / data science theory, techniques, and tools
• Scientific thinking, ability to work with literature and the ability to implement complex projects
• Willingness 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
• Curious, hardworking, detail-oriented and motivated by complex analytical problems

 

 

Preferred qualifications, capabilities and skills

• Solid time series analysis, machine learning or financial engineering background.
• Strong background in Mathematics and Statistics.
• Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal.
• Experience designing and performance tuning large scale distributed systems.
• Contribution to open-source projects on Machine Learning.
• Knowledge in Reinforcement Learning or Meta Learning.
• Experience with frameworks for distributed machine learning such as Ray, etc.

 

About MLCOE
The Machine Learning Center of Excellence (MCLOE) team partners across the firm to create and share Machine Learning Solutions for our most challenging business problems. In this role you will work and collaborate with a team comprised of a multi-disciplinary community of experts focused exclusively on Machine Learning. On this team you will work with cutting-edge techniques in disciplines such as Deep Learning and Reinforcement Learning

For more information about the MLCOE, please visit http://www.jpmorgan.com/mlcoe.  To learn about how we're using AI/ML to drive transformational change, please read this blog: https://www.jpmorgan.com/insights/technology/technology-blog?source=cib_di_jp_aBtechblog102

 

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.

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
   We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.