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JPMorganChase

Applied AI/ML Modeling - Senior Associate

Posted 5 Days Ago
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Hybrid
New York, NY, USA
Senior level
Hybrid
New York, NY, USA
Senior level
Develop and deploy AI/ML models for consumer banking use cases including lead scoring, next-best-action, retention, cross-sell, and customer prioritization. Define success metrics, analyze complex datasets, communicate recommendations to nontechnical stakeholders, and partner with product, technology, governance, risk, and operations teams. Ensure models meet regulatory and model risk standards through documentation, monitoring, drift detection, and retraining.
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Our Consumer Bank AI Modeling team develops advanced analytics and machine learning solutions that inform high-impact decisions across field workforce effectiveness, customer engagement, and banker-led growth.

As an Applied AI Modeling Senior Associate in the Consumer Bank AI Modeling team, you will build and deploy advanced AI/ML models that measurably improve banker sales effectiveness and customer outcomes. Your models will help bankers deliver the right outreach at the right time to our customers, driving deposit growth, increasing customer retention, and strengthening relationships. You will operate in a highly governed environment and partner closely with product, UX, operations, and technology teams to translate modeling innovation into field-ready tools that bankers trust and adopt.

Job responsibilities

  • Develop and launch AI/ML models that solve complex, ambiguous business problems in Consumer Banking, with emphasis on sales effectiveness and banker enablement (e.g., lead scoring, propensity modeling, next-best-action/next-best-offer, customer prioritization, retention, and cross-sell) using techniques such as deep learning, causal inference, contextual bandits, reinforcement learning, and constrained optimization.
  • Participate in modeling engagements end-to-end, including scoping use cases with business partners, defining success metrics (incrementality, ROI, adoption), building project plans, and working with large, complex datasets to formulate testable hypotheses.
  • Translate model outputs into clear, actionable recommendations for non-technical partners, and produce narratives that drive adoption (why this lead, why now, what action, expected outcome).
  • Partner with governance, risk, and controls teams to expedite fair and thorough model reviews, document model intent and limitations, monitor performance and drift, and maintain adherence to regulatory and model risk management standards.

Required qualifications, capabilities, and skills

  • Advanced degree (Master’s or Ph.D.) in a quantitative discipline such as Computer Science, Statistics, Machine Learning, Econometrics, Operations Research, Applied Mathematics, or a related field.
  • 3+ years of hands-on, relevant industry experience developing and deploying AI/ML models in production, including statistical modeling and modern Machine Learning.
  • Proficient in Python with hands-on experience in ML/deep learning frameworks (TensorFlow, PyTorch) and core libraries (NumPy, Scikit-Learn, Pandas). Strong working knowledge of notebooks and cloud-based development/compute.
  • Deep expertise in at least one of the following, with meaningful exposure to at least one other: 
    • Recommendation/decisioning systems (next-best-action/offer), ranking, and constrained optimization
    • Causal inference and uplift / treatment effect modeling for targeted interventions
    • Online learning approaches (contextual bandits, multi-armed bandits, reinforcement learning)
    • Behavioral modeling and human-in-the-loop systems that drive adoption and performance
  • Demonstrated ability to communicate complex modeling concepts clearly to non-technical stakeholders and drive decisions.

Preferred qualifications, capabilities, and skills

  • Ph.D. in a relevant discipline.
  • Experience developing advanced AI/ML models in consumer finance, fintech, retail, marketplaces, or other high-scale customer engagement environments.
  • Experience with at least one of the following: 
    • Decisioning/online learning libraries (e.g., Vowpal Wabbit, RLlib, Stable Baselines) or large-scale ranking/recommendation tooling
    • Causal inference tooling and experimentation platforms (A/B testing, CUPED, synthetic controls, causal forests, doubly robust methods)
  • Familiarity with behavioral science concepts (choice architecture, friction, habit formation) and designing interventions that are effective and compliant.
  • Experience with Databricks, Snowflake, or similar platforms; strong practical MLOps experience (model deployment patterns, monitoring, drift detection, retraining, and reproducibility).
About Us

Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

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 they 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.

Equal Opportunity Employer/Disability/Veterans

About the Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.
HQ

JPMorganChase New York, New York, USA Office

270 Park Avenue, New York, NY, United States, 10017-2014

JPMorganChase New York, New York, USA Office

4 Metrotech Center, New York, NY, United States, 11201

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