Applied AI/ML Modeling - Senior Associate
Salary not listed • NY, United States • Full-time
Posted 25d ago
No salary is listed. Many US states require employers to post a pay range, so ask about pay early.
Job Location
NY, United States
Also open in New York, NY, United States
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
Our Branch Network Modeling team develops advanced analytics and machine learning solutions that inform high-impact decisions across physical location strategy and field workforce effectiveness. As an Applied AI Modeling Senior Associate, you will build advanced artificial intelligence (AI) and machine learning (ML) models that directly shape high-stakes decisions impacting Chase’s branch network and the bankers who serve our customers. Your models will help optimize our branch network, using geospatial AI and graph-based models to determine where Chase should invest, grow, or reposition its physical footprint, or will empower our bankers in the field to serve our customers using techniques like reinforcement learning and behavioral science.
Responsibilities
- Develop and launch AI and ML models to solve complex business problems in Consumer Banking, including retail network optimization, investment optimization, resource allocation, and sales effectiveness.
- Manage modeling engagements end-to-end, including stakeholder communication, defining business use cases, project planning, and working with large datasets (geospatial, transactional, behavioral) to formulate hypotheses.
- Translate technical model outputs into actionable recommendations for non-technical business partners.
- Partner with governance teams to ensure fair model reviews, track performance, and maintain regulatory compliance.
Requirements
- Advanced degree (Master's or PhD) in a quantitative or spatial discipline (e.g., Computer Science, Statistics, Machine Learning, Operations Research, Applied Mathematics, Geography).
- 3+ years of hands-on industry experience in developing and deploying AI/ML models, including statistical modeling, ML, reinforcement learning, or optimization algorithms.
- Proficient in Python with experience in ML and deep learning frameworks (TensorFlow, PyTorch) and libraries (NumPy, Scikit-Learn, Pandas).
- Strong working knowledge of Jupyter Notebook/Lab and cloud computing.
- Deep expertise in at least one of: Geospatial analytics, spatial statistics, or spatial optimization.
- Deep expertise in at least one of: Graph neural networks, network science, or graph-based optimization.
- Deep expertise in at least one of: Reinforcement learning, multi-armed bandits, or online/continuous learning.
- Deep expertise in at least one of: Behavioral modeling, adaptive intervention design, or human performance optimization.
- Meaningful exposure to at least one additional area from the expertise list.