Applied AI/ML Modeling - Vice President

JPMorganChase; New York (NY); On-site; USD 130,000 - 180,000; Full time

Job summary

A leading financial services firm seeks an Applied AI Modeling Vice President to develop advanced AI and machine learning models for optimizing its branch network in New York. Candidates should have an advanced degree in a quantitative discipline, at least 4 years of experience in AI/ML, and proficiency in Python with familiarities in TensorFlow and PyTorch. The role involves working with geospatial data and translating technical outputs for business stakeholders.

Qualifications

• Master's or PhD in a quantitative or spatial discipline such as Machine Learning or Applied Mathematics.
• 4+ years of experience in developing and deploying AI/ML models.
• Proficient in Python with experience in ML frameworks and libraries.

Responsibilities

• Develop AI and ML models to solve complex business problems in Consumer Banking.
• Lead modeling engagements with stakeholders and analyze large datasets.
• Translate model outputs into actionable recommendations for non-technical partners.

Skills

Machine Learning

Python

Geospatial analytics

Deep learning frameworks

Spatial optimization

Behavioral modeling

Education

Advanced degree in a quantitative or spatial discipline

Tools

TensorFlow

PyTorch

NumPy

Scikit-Learn

Pandas

Jupyter Notebook Lab

GeoPandas

Job description

Position Overview

Applied AI Modeling Vice President in Branch Network Modeling team. Build advanced AI and machine learning 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, and empower our bankers in the field to serve customers using techniques such as reinforcement learning and behavioral science.

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.
• Lead 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

• 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.
• 4+ 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

• 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.

Equal Opportunity Employer / Disability / Veterans

We are an equal opportunity employer and place a high value on diversity and inclusion. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.