Job Description

Job responsibilities

• Research and develop novel alpha signals using traditional and alternative data sources to enhance return forecasting models.
• Improve return forecasting models and portfolio construction frameworks for global equity markets, applying reinforcement learning and advanced machine learning techniques.
• Apply statistical, econometric, and machine learning methods to large, complex datasets to extract actionable insights.
• Collaborate with technology teams to integrate research models into production systems and ensure robust implementation.
• Partner with portfolio managers and stakeholders to translate quantitative research into investment decisions.
• Stay current with academic and industry developments in quantitative finance, machine learning, and data science.
• Present complex research findings clearly to both technical and non-technical audiences.
• Contribute to a collaborative team environment and support continuous learning and innovation.

Required qualifications, capabilities, and skills

• PhD in machine learning, computer science, statistics, or a related quantitative discipline; specialization in reinforcement learning highly desirable.
• 0–3 years of experience in quantitative research, data science, or a related field (industry or academic).
• Strong programming skills in Python and experience with machine learning libraries.
• Familiarity with quantitative modeling, portfolio construction, and equity markets.
• Experience working with large, complex, and alternative datasets.
• Excellent verbal and written communication skills, with the ability to present complex ideas to technical and non-technical audiences.
• Demonstrated ability to work effectively in a team environment.
• Strong problem-solving skills, intellectual curiosity, and ability to drive research projects independently.

Preferred qualifications, capabilities, and skills

• Experience integrating research models into production investment systems.
• Background in developing and implementing reinforcement learning techniques in finance.
• Experience collaborating with portfolio managers and technologists.
• Track record of publishing or presenting research in quantitative finance or machine learning.

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.