Machine Learning Expert - Time Series And Reinforcement Learning Group - Vice President - Machine Learning Center Of Excellence

JobID: 210494369

Category: Predictive Science

JobSchedule: Full time

Posted Date: 2024-03-12T14:39:34+00:00

JobShift: Day

Base Pay/Salary: New York,NY $147,250.00-$260,000.00; Palo Alto,CA $147,250.00-$260,000.00; Seattle,WA $147,250.00-$260,000.00

Applied AI ML opportunities are available at Sr. Associate, Vice President and Executive Director level in New York location. This role offers a unique opportunity to explore novel and complex challenges that could profoundly transform how the bank operates.

Machine Learning Expert

• Time Series and Reinforcement Learning group

• VP

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 Job

The successful candidate 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. 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 center 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, minimum 3 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

• 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

• Curious, hardworking, detail-oriented and motivated by complex analytical problems

Preferred qualifications, capabilities, and skills

• Solid time series analysis, speech recognition, NLP 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 with GPUs and cloud-based training of deep neural networks.

• Contribution to open-source projects on Machine Learning.

• Knowledge in Reinforcement Learning or Meta Learning.

• Experience with big-data technologies such as Hadoop, Spark, SparkML, etc