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.

As a Machine Learning Scientist - Speech AI and NLP - Vice President within the Machine Learning Center of Excellence, you will have the opportunity to apply sophisticated machine learning methods to complex tasks including natural language processing, speech analytics, time series, reinforcement learning and recommendation systems. You will collaborate with various teams and actively participate in our knowledge sharing community. We are looking for someone who excels in a highly collaborative environment, working together with our business, technologists and control partners to deploy solutions into production. If you have a strong passion for machine learning and enjoy investing time towards learning, researching and experimenting with new innovations in the field, this role is for you. We value solid expertise in Deep Learning with hands-on implementation experience, strong analytical thinking, a deep desire to learn and high motivation.

Job Responsibilities

Research, develop and productionize high performance machine learning models, quantitative models, and applications. Collaborate with all of JPMorgan's lines of business and functions to deliver software solutions, making high technology and business impact. Design and implement highly scalable and reliable data processing pipelines and perform analysis and insights to drive and optimize business result.

 Required qualifications, capabilities, and skills

PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science with three years of industry experience Or an MS with at least five years of industry or research experience in the field Solid background in NLP or speech recognition and analytics, personalization/recommendation and hands-on experience and solid understanding of machine learning and deep learning methods Extensive experience with machine learning and deep learning toolkits  (e.g.: TensorFlow, PyTorch) Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. Curious, hardworking and detail-oriented, and motivated by complex analytical problems

Preferred qualifications, capabilities, and skills

Strong background in Mathematics and Statistics Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal Knowledge in Deep Learning frameworks Cloud computing: Google Cloud, Amazon Web Service, Azure, Docker, Kubernetes. Experience in distributed system design and development