In this role, you'll be the analytical expert for identifying and retooling suitable machine learning algorithms that can enhance the fraud risk ranking of particular transactions and/or applications for new products. This includes a balance of feature engineering, feature selection, and developing and training machine learning algorithms using cutting edge technology to extract predictive models/patterns from data gathered for billions of transactions. Your expertise and insights will help us effectively utilize big data platforms, data assets, and analytical capabilities to control fraud loss and improve customer experience.
You'll work in an industrial R&D/skunkworks environment, developing innovative predictive models on a dataset in the hundreds of TBs and higher. As there are no known model architectures that are effective on fraud datasets in general, you'll need to develop them.
Master's degree in Mathematics, Statistics, Economics, Computer Science, Operations Research, Physics, and other related quantitative fields
At least one year of experience with data analysis in Python
Experience in designing models for a commercial purpose using some (at least 3) of the following machine learning and optimization techniques: CNN, RNN, SVM, Reinforcement Learning, Random Forest/GBM
A strong interest in how models work, the reasons why particular models work or not work on particular problems, and the practical aspects of how new models are designed
PhD in a quantitative field with publications in top journals, preferably in machine learning
Experience with model design in a big data environment making use of distributed/parallel processing via Hadoop, particularly Spark and Hive
Experience designing models with Keras/TensorFlow on GPU-accelerated hardwareJPMorgan Chase & Co., 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 management.
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. In accordance with applicable law, we make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as any mental health or physical disability needs.