below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$145,200–$214,500.
Based on 240 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1219 open roles
on FindRole.
As an Applied AI/ML Modeling - Senior Associate in the Branch Network Modeling team, you will develop and launch advanced artificial intelligence and machine learning models to solve complex business problems in Consumer Banking. You will participate in end-to-end modeling engagements, working with large datasets including geospatial, demographic, transactional, and behavioral data to optimize retail networks, resource allocation, and sales effectiveness. Your work involves using techniques like reinforcement learning, graph-based models, and geospatial AI to determine physical footprint investments and empower field bankers. You must be proficient in Python, TensorFlow, PyTorch, NumPy, Scikit-Learn, and Pandas, with experience in cloud computing and Jupyter. Key expertise includes spatial statistics, graph neural networks, multi-armed bandits, and behavioral modeling to provide actionable recommendations for real estate and finance partners.
Develop and launch AI and ML models to solve complex business problems in retail network optimization and resource allocation.
Build geospatial AI and graph-based models to determine physical footprint investments and growth strategies.
Create reinforcement learning and behavioral science models to improve field banker effectiveness and customer service.
Manage end-to-end modeling engagements by formulating testable hypotheses from large geospatial, demographic, and transactional datasets.
Translate technical model outputs into actionable recommendations for non-technical partners in Real Estate, Finance, and Market Strategy.
Partner with governance teams to conduct model reviews and ensure adherence to regulatory compliance standards.
Track and maintain performance metrics for all deployed machine learning models.
What we're looking for
Master’s or PhD in a quantitative or spatial discipline such as Computer Science, Statistics, Machine Learning, Operations Research, Applied Mathematics, or Geography.
3+ years of hands-on industry experience developing and deploying AI/ML models, including statistical modeling, reinforcement learning, or optimization algorithms.
Proficiency in Python with hands-on experience in ML and deep learning frameworks like TensorFlow or PyTorch and libraries like NumPy, Scikit-Learn, and Pandas.
Strong working knowledge of Jupyter Notebook/Lab and cloud computing.
Deep expertise in at least one of geospatial analytics, graph neural networks, reinforcement learning, or behavioral modeling, with exposure to at least one other.
Hold a PhD in a relevant discipline (preferred).
Experience developing advanced AI or ML models in consumer finance, logistics, major retailers, or AI-native platforms (preferred).
Experience with specific geospatial tools, graph ML frameworks, RL libraries, behavioral science concepts, or platforms like Databricks and Snowflake (preferred).
Python
Machine Learning
Optimization
Natural Language Processing
Spark
Hadoop
big-data
Regression
Classification
Recommender Systems
Neural Language Modeling
Data Science
Python
SQL
LLMs
Snowflake
Tableau
AWS
Machine Learning
Data Engineering
Data Science
Generative AI
Multi-agent patterns
Data Pipelines
Quantitative Research