Applied AIML, Executive Director

Applied AI/ML Executive Director Base Pay Range

$/yr - $/yr

As an Applied AI/ML Executive Director within our dynamic team, you will apply your quantitative, data science, and analytical skills to complex problems. You will 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.

• Develop state-of-the art machine learning models to solve real-world problems and apply them to tasks such as natural language processing (NLP), speech recognition and analytics, time-series predictions or recommendation systems.
• Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production.
• Coaching other AI/ML team members towards both personal and professional success.

• PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science; or with at least 5 years of industry experience or an MS with at least 7 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., Tensor Flow, PyTorch, Num Py, Scikit-Learn, Pandas).
• 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.
• Curious, hardworking and detail‑oriented, and motivated by complex analytical problems.

• Strong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test development.
• Knowledge in search/ranking, Reinforcement Learning or Meta Learning.
• Experience with A/B experimentation and data/metric-driven product development, cloud‑native deployment in a large scale distributed environment and ability to develop and debug production‑quality code.
• Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal.

J.P. Morgan Asset & Wealth Management delivers industry‑leading investment management and private banking solutions. Asset Management provides individuals, advisors and institutions with strategies and expertise that span the full spectrum of asset classes through our global network of investment professionals. Wealth Management helps individuals, families and foundations take a more intentional approach to their wealth or finances to better define, focus and realize their goals.

JPMorgan Chase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset…