Applied AI/ML Modeling - Senior Associate

Posted Yesterday
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2 Locations
Hybrid
Senior level
Financial Services
We’re one of the world’s biggest technology-driven companies
The Role
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.
Summary Generated by Built In

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.

Skills Required

  • Master’s or Ph.D. in computer science, statistics, machine learning, econometrics, operations research, applied mathematics, or a related quantitative discipline
  • At least 3 years of hands-on industry experience developing and deploying production AI/ML models
  • Experience with statistical modeling and modern machine learning
  • Proficiency in Python
  • Hands-on experience with TensorFlow, PyTorch, NumPy, Scikit-Learn, and Pandas
  • Strong working knowledge of notebooks and cloud-based development or compute
  • Deep expertise in recommendation or decisioning systems, causal inference, online learning, behavioral modeling, or human-in-the-loop systems
  • Meaningful exposure to at least one additional AI/ML specialization listed in the job description
  • Ability to communicate complex modeling concepts clearly to nontechnical stakeholders and drive decisions
  • Ph.D. in a relevant discipline
  • Experience developing AI/ML models in consumer finance, fintech, retail, marketplaces, or high-scale customer engagement environments
  • Experience with decisioning or online learning libraries, ranking, or recommendation tooling
  • Experience with causal inference tooling or experimentation platforms
  • Familiarity with behavioral science concepts and compliant intervention design
  • Experience with Databricks, Snowflake, or similar platforms
  • Practical MLOps experience including deployment, monitoring, drift detection, retraining, and reproducibility

JPMorganChase Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.

  • Healthcare Strength — Medical, dental, vision, and mental-health coverage are broad, with wellness incentives, on-site or virtual care, and an EAP offering coaching and counseling. Plan materials emphasize accessible options, including multiple medical choices and tools to manage costs.
  • Parental & Family Support — Paid parental leave extends up to 16 weeks for all parents, supplemented by paid Critical Caregiver Leave. Family resources include backup childcare via Bright Horizons, lactation support and milk-shipping, family-building assistance, and even a free five-month SNOO rental for newborns.
  • Retirement Support — Retirement programs include a 401(k) with an annual company match and automatic pay credits for most employees, with a legacy pension available to earlier hires. An Employee Stock Purchase Plan at a 5% discount further supports long-term savings.

JPMorganChase Insights

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The Company
HQ: New York, NY
289,097 Employees
Year Founded: 1799

What We Do

JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.

Why Work With Us

Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.

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