This listing doesn't post a salary. Most similar roles pay
$158,212–$247,731.
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
1117 open roles
on FindRole.
Listed pay typically runs
$186,160–$215,000
across 7 roles with salary data.
As an Applied AI/ML Modeling - Vice President on the Branch Network Modeling team, you will develop advanced artificial intelligence and machine learning models to inform high-impact decisions regarding physical location strategy and field workforce effectiveness. You will build models using geospatial AI, graph-based models, reinforcement learning, and behavioral science to optimize the branch network and empower bankers in the field. Your daily work involves leading end-to-end modeling engagements, managing complex datasets including demographic and transactional data, and translating technical outputs into actionable recommendations for non-technical partners. You will utilize Python, TensorFlow, PyTorch, NumPy, Scikit-Learn, and Pandas within cloud computing environments. Required expertise includes spatial statistics, graph neural networks, or multi-armed bandits. The role addresses critical business problems in consumer banking, specifically retail network optimization, resource allocation, and sales effectiveness.
Develop and launch AI and ML models to solve complex problems in retail network optimization and resource allocation.
Build geospatial AI and graph-based models to determine physical footprint investments and growth strategies.
Implement reinforcement learning and behavioral science techniques to improve field banker effectiveness.
Manage modeling engagements end-to-end by translating business needs into testable hypotheses using large, complex datasets.
Translate technical model outputs into actionable recommendations for non-technical partners in Real Estate, Finance, and Market Strategy.
Partner with governance teams to ensure models meet regulatory compliance standards and pass thorough reviews.
Track performance metrics and maintain high standards for model accuracy and fairness.
What we're looking for
Master's degree or PhD in a quantitative or spatial discipline such as Computer Science, Statistics, Machine Learning, Operations Research, Applied Mathematics, or Geography.
4+ years of experience developing and deploying AI/ML models, including statistical modeling, reinforcement learning, or optimization algorithms.
Proficiency in Python with hands-on experience in ML/deep learning frameworks like TensorFlow and PyTorch.
Working knowledge of Jupyter Notebook/Lab and cloud computing environments.
Expertise in at least one area: geospatial analytics, graph neural networks, reinforcement learning, or behavioral modeling.
Experience developing advanced AI models in consumer finance, logistics, major retail, or AI-native platforms.
Familiarity with specialized tools such as GeoPandas, PyTorch Geometric, RLlib, Databricks, or Snowflake.
Ability to translate technical model outputs into actionable recommendations for non-technical business partners.
Machine Learning
Deep Learning
Generative AI
LLMs
NLP
Python
Java
C++
Transformers
Hugging Face
TensorFlow
PyTorch
NumPy
Scikit-Learn
Pandas
AWS
SageMaker
Prompt Engineering
Big Data
Generative AI
Machine Learning
Agentic AI
Model Governance
Model Risk Management
Agile
Technical Program Management
Data Governance
Model Development Lifecycle
Risk Mitigation
Process Improvement
Data Management
Machine Learning
Artificial Intelligence
Python
R
Scala
Hadoop
Spark
SparkML
SQL
Hive
AWS
Azure
Google Cloud Platform
Natural Language Processing
Time Series
Optimization
Operations Research
Statistics