Join a team where your ideas shape the future of digital payments and financial security. You will tackle complex challenges, work with cutting-edge technology, and collaborate with talented peers in a culture that values creativity, ownership, and impact. Accelerate your career while making a difference for millions of users worldwide. Operating in over 160 countries and handling more than 120 currencies, we are the largest processor of USD payments, with a daily transaction volume of $10 trillion. 

As an Applied AI ML Scientist, you will design, build, and deploy advanced machine learning models that drive the safety and reliability of our payments platform. You will operate at the intersection of research and production, taking full ownership of model performance from concept to deployment. You will collaborate with scientists and engineers who thrive on innovation, and your work will directly influence the future of digital payments and financial security. 

Job Responsibilities: 

• Develop, train, and deploy machine learning models for fraud prevention and risk management in a fast-paced, collaborative environment. 

• Research and implement novel architectures, including Graph Neural Networks and Large Language Models, within the payments space. 

• Build and maintain data pipelines for model training and evaluation using industry-leading tools. 

• Monitor and optimize model performance in real-world environments, adapting to evolving fraud patterns. 

• Lead technical strategy and guide analytical direction within the team, fostering a culture of innovation. 

• Collaborate with cross-functional teams, including product, engineering, and data science, to align modeling solutions with business objectives. 

• Contribute to the continuous improvement of our machine learning stack and best practices. 

Required qualifications, capabilities, and skills: 

• Master’s degree in Computer Science, Mathematics, Statistics, Physics, or a related quantitative field, or equivalent work experience. 

• Possess a deep understanding of machine learning theory and algorithms. 

• Proficient in Python, with experience in deep learning frameworks such as PyTorch or TensorFlow, as well as classical machine learning tools like XGBoost or Scikit-learn. 

• Hands-on experience working with large datasets using data engineering tools such as Spark, Databricks, or Snowflake, and will work with one of the largest sets of payments data. 

• Proven track record of building and maintaining models in a business-critical environment, directly influencing money movement across the globe. 

Preferred qualifications, capabilities, and skills: 

• Deeply technical and understand the mathematics behind the algorithms, not just how to import the library. 

• Product-first mindset, focusing beyond model performance and taking responsibility for the product as a whole, understanding the role models play in the user experience. 

• Versatile modeler, able to seamlessly handle both tabular and non-tabular data using classical machine learning (e.g., trees/forests) and modern deep learning techniques. 

• Driven by impact and energized by the responsibility of having your models make decisions on live financial transactions. 

 FEDERAL DEPOSIT INSURANCE ACT:

This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase’s review of criminal conviction history, including pretrial diversions or program entries.