Applied AI ML Associate - Payments Operations

Our team is responsible for pushing innovations in the Payments space, which is a cornerstone of JPMorgan Chase business. Payments are at the center of the global economy, connecting businesses and consumers around the world. In recent years, the payments industry has experienced rapid innovation with new technologies entering the market. As part of our Applied AI ML team, you'll be at the forefront of this transformation, developing machine learning solutions with real impact on global finance.

As an Applied AI ML Associate in our Payments Operations team, you will be responsible for proposing, developing, testing, deploying, and monitoring machine learning applications and models that support the Payments Operations strategy. You will work closely with other team members as well as with a diversity of stakeholders to develop solutions that bring lasting benefit to the business regardless of the latest research trend. This role requires strong software engineering skills, critical thinking about data and applications, and the ability to translate business needs into technical solutions.

• Identify automation opportunities by gathering business knowledge from stakeholders, exploring large volumes of complex data, and testing hypothesis using traditional and cutting-edge machine learning models.
• Propose and implement innovative approaches to process multimodal data to enhance business insights and power machine learning models.
• Design and build machine learning models in partnership with different parts of the business, by understanding key challenges and metrics of success, communicating results, and gathering feedback to improve model performance and expectations.
• Productionize and evaluate models, ensuring compliance with relevant processes and governance.

• BS degree in Computer Science, Mathematics, Engineering, or related field with 3+ years of experience, or MS in a related field.
• Proficient in Python, R, or other equivalent languages, including experience using machine learning frameworks such as Scikit-Learn, TensorFlow, Pytorch, as well as version control, testing and object-oriented programming.
• Strong mathematical and statistical skills, including knowledge of exploratory data analysis, statistical models, GLM, decision trees, clustering, and bootstrapping.
• Experience with deep learning for language and image classification, image to text extraction, and knowledge of CNNs, RNNs and Transformers.
• Ability to manage AI/ML project from inception to production, including extraction of insights, planning and completion of milestones, iteration on solutions and evaluation of business tradeoffs.
• Eagerness to work with large and complex datasets, including preprocessing raw and unlabeled multimodal data.
• Excellent communication and presentation skills that enable collaboration and transparency with non-technical senior leaders as well as technical counterparts.
• Self-motivated and comfortable working with a geographically distributed team.

• Experience with Natural Language Processing (NLP), Language Models, and Computer Vision.
• Ability to design intrinsic and extrinsic evaluations of a model's performance aligned with business goals.