Applied AI/ML Modeling - Senior Associate

JPMorgan Chase & Co.; United States; Presencial; USD 150 000 - 230 000; Tempo integral

Resumo da oferta

JPMorgan Chase & Co. is seeking an Applied AI Modeling Senior Associate in Branch Network Modeling to build AI and ML models that shape branch network decisions and guide where the bank invests and positions its physical footprint.

You will work with geospatial AI, graph-based models, and reinforcement learning to empower bankers in the field while delivering testable business hypotheses and clear recommendations to cross-functional partners.

Qualificações

• Advanced degree in a quantitative or spatial discipline such as Computer Science, Statistics, Machine Learning, Operations Research, Applied Mathematics, or Geography.
• 3+ years of hands-on, relevant industry experience in developing and deploying AI/ML models including statistical modeling, ML, reinforcement learning, or optimization algorithms.
• Proficient in Python with hands-on 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 the following, with meaningful exposure to at least one other: Geospatial analytics, Graph neural networks, Reinforcement learning, Behavioral modeling, adaptive intervention design, or online learning.

Responsabilidades

• Develop and launch AI and ML models that solve complex, ambiguous business problems in Consumer Banking, spanning areas such as retail network optimization, investment optimization, resource allocation, and sales effectiveness.
• Participate in modeling engagements end-to-end, including interfacing with business, governance, UX, and technology stakeholders; articulating clear business use cases; delivering on project plans; and working with large, complex datasets — including geospatial, demographic, transactional, and behavioral data — to formulate testable business hypotheses.
• Translate technical model outputs into clear, actionable recommendations for non-technical business partners in Real Estate, Finance, and Market Strategy.
• Partner with governance teams to expedite fair and thorough model reviews, track performance metrics, and maintain adherence to regulatory compliance standards.

Conhecimentos

Python programming

ML frameworks

Geospatial analytics

Graph neural networks

Reinforcement learning

Cloud computing

Formação académica

Master’s or PhD in a quantitative or spatial discipline

Ferramentas

GeoPandas

PySAL

H3

Esri/ArcGIS

Carto

PyTorch Geometric

DGL

NetworkX

RLlib

Stable Baselines

Vowpal Wabbit

Descrição da oferta de emprego

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 in Branch Network Modeling team, 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.

Job responsibilities

• Develop and launch AI and ML models that solve complex, ambiguous business problems in Consumer Banking, spanning areas such as retail network optimization, investment optimization, resource allocation, and sales effectiveness.
• Participate in modeling engagements end-to-end, including interfacing with business, governance, UX, and technology stakeholders; articulating clear business use cases; delivering on project plans; and working with large, complex datasets — including geospatial, demographic, transactional, and behavioral data — to formulate testable business hypotheses.
• Translate technical model outputs into clear, actionable recommendations for non-technical business partners in Real Estate, Finance, and Market Strategy.
• Partner with governance teams to expedite fair and thorough model reviews, track performance metrics, and maintain adherence to regulatory compliance standards.

Required qualifications, capabilities, and skills

• Advanced degree (master’s or PhD) in a quantitative or spatial discipline such as Computer Science, Statistics, Machine Learning, Operations Research, Applied Mathematics, or Geography, or a related field.
• 3+ years of hands‑on, relevant industry experience in developing and deploying AI/ML models, including statistical modeling, ML, reinforcement learning, or optimization algorithms.
• Proficient in Python with hands‑on experience in ML and deep learning frameworks (TensorFlow, PyTorch) and libraries (e.g., NumPy, Scikit-Learn, Pandas). Strong working knowledge of Jupyter Notebook/Lab and cloud computing.
• Deep expertise in at least one of the following, with meaningful exposure to at least one other:

Geospatial analytics, spatial statistics, or spatial optimization

• Graph neural networks, network science, or graph-based optimization
• Reinforcement learning, multi‑armed bandits, or online/continuous learning
• Behavioral modeling, adaptive intervention design, or human performance optimization

Preferred qualifications, capabilities, and skills

• Hold a PhD in a relevant discipline.
• Experience developing advanced AI or ML models in consumer finance, logistics, major retailers, or AI‑native platforms.
• Experience with at least one of the following: geospatial tools and libraries (e.g., GeoPandas, PySAL, H3, Esri/ArcGIS, Carto, Wherobots, QGIS), graph ML frameworks (e.g., PyTorch Geometric, DGL, NetworkX), RL libraries (e.g., RLlib, Stable Baselines, Vowpal Wabbit).
• Familiarity with behavioral science concepts (e.g., nudge theory, decision theory) or experience building adaptive, continuous learning, or recommendation systems.
• Experience with Databricks, Snowflake, or similar platforms.