Applied AI/ML Associate
About The Position
As a Risk program Senior Associate within the Chase consumer Bank, 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. Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
Requirements
- Master's degree in Mathematics, Statistics, Economics, Computer Science, Operations Research, Physics, and other related quantitative fields.
- 2+ years 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: deep learning, Natural Language Processing (NLP), graph algorithms, GNN, 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.
Nice To Haves
- PhD in a quantitative field with publications in top journals, preferably in machine learning.
- Experience with model development in a cloud environment such as AWS SageMaker, GCP Vertex AI or Azure Machine Learning.
- Experience of developing models with Keras/Pytorch/TensorFlow on GPU-accelerated hardware.
Responsibilities
- Identify and retool machine learning (ML) algorithms to analyze datasets for fraud detection in the Chase Consumer Bank.
- Perform machine learning tasks such as feature engineering, feature selection, and developing and training machine learning algorithms using cutting-edge technology to extract predictive models/patterns from billions of transactions’ amounts of data.
- Collaborate with business teams to identify opportunities, collect business needs, and provide guidance on leveraging the machine learning solutions.
- Interact with a broader audience in the firm to share knowledge, disseminate findings, and provide domain expertise
Benefits
- We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
5,001-10,000 employees
