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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 Vice President in Branch Network Modeling team, you will build advanced artificial intelligence (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, or will empower our bankers in the field to serve our customers using techniques like reinforcement learning and behavioral science.

• 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.

• 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.
• 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

• 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.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission‑based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on‑site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

We recognize that our people are our strength and the diverse talents we bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. 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. Visit our FAQs for more information about requesting an accommodation.