Applied AI ML [Multiple Positions Available]

Description Duties: Design and develop machine learning models to drive impactful decisions for the card business throughout the customer lifecycle involving acquisition, account management, transaction authorization, and collection. Utilize cutting‑edge machine learning approaches and construct sophisticated machine learning models including deep learning architecture on big data platforms. Work closely with the senior management team to develop ambitious, innovative modeling solutions and deliver them into production. Collaborate with various partners in marketing, risk, technology, and model governance, throughout the entire modeling lifecycle involving development, review, deployment, and use of the models. Present Model result and Adhoc research to senior leaders. Qualifications Minimum education and experience required: Master’s degree in Financial Engineering, Mathematics, Statistics, or related field of study plus 3 years of experience in the job offered or as Applied AI ML, Software Developer, Risk Technology, Quantitative Analytics, or related occupation. The employer will alternatively accept a Bachelor’s degree in Financial Engineering, Mathematics, Statistics, or related field of study plus 5 years of experience in the job offered or as Applied AI ML, Software Developer, Risk Technology, Quantitative Analytics, or related occupation. Skills Required This position requires three (3) years of experience with the following: Python programming, focused on data manipulation, analysis, and machine‑learning libraries including Pandas, NumPy, Scikit‑learn, and PyTorch; object‑oriented software development in C#, contributing to design and maintenance of production‑grade systems for financial data workflows. This position requires two (2) years of experience with the following: developing predictive models and working with cloud‑based solutions on financial datasets, using machine‑learning techniques including logistic regression, gradient boosting, and decision trees; deep learning solutions including LSTM networks and transformer‑based models, BERT to extract insights from financial datasets; economic and econometrics modeling and data mining, using regression, principal‑component analysis, and time series methods. This position requires any amount of experience with the following: programming in MATLAB and R for statistical analysis and rapid prototyping; financial model governance frameworks and regulatory compliance standards. Job Location 301 North Walnut Street, Wilmington, DE 19801. Full‑Time. #J-18808-Ljbffr JPMorgan Chase & Co.