Executive Director, AI/ML — Forecasting, Constraint Optimization, and Recommendation Systems

JP Morgan Chase; Palo Alto (CA); On-site; USD 223,000 - 325,000; Full time

Job summary

JP Morgan Chase seeks an Executive Director of AI/ML to lead forecasting, constraint optimization, and recommendation systems across NY and Palo Alto. You will own end-to-end AI/ML ecosystems, drive business outcomes, and coordinate with executives, product, data, and engineering teams.

The role combines hands-on technical leadership with strategy, model development, deployment, and ongoing production operations, emphasizing reliability and stakeholder alignment.

Qualifications

• PhD in AI/OR or related quantitative field with strong AI/ML and constraint optimization background.
• Outstanding business stakeholder management and written/oral communication capable of influencing executives across product, business, and analytics.
• Extensive hands-on experience deploying large-scale AI/ML systems including time-series forecasting, demand prediction, and recommendation systems.
• Deep expertise in mathematical/constraint optimization including objective formulation and solver selection.
• Advanced programming skills with 10+ years of combined doctoral/industry experience in multiple languages.
• Strong CS background in data structures, algorithms, OS, databases, and scalable data systems.

Responsibilities

• Lead the design and delivery of a complex constraint-optimization and recommendation system translating forecasts into actionable decisions.
• Formulate global optimization objectives and constraints with business partners; address trade-offs and capacity limits.
• Develop and validate time-series and demand-driven predictive models and integrate outputs into optimization workflows.
• Build and lead a multidisciplinary AI/ML team; provide technical and career guidance.
• Manage executive-level stakeholder communications and align priorities across cross-functional teams.
• Own production operation: monitoring, drift detection, retraining, incident resolution, and reliability improvements.
• Drive complete product/tech lifecycle from problem definition to deployment and performance evaluation.
• Serve as hands-on architect and coder for end-to-end data systems, forecasting services, and optimization engines.
• Foster continuous learning and knowledge sharing within the organization.

Skills

Stakeholder management

Communication skills

AI/ML systems

Constraint optimization

Programming skills

Distributed computing

Data systems architecture

Education

PhD in Computer Science

Tools

Python

Spark

Scala

Java

Job description

Executive Director, AI/ML — Forecasting, Constraint Optimization, and Recommendation Systems

New York, NY, United States

and 1 more

Job Information

• Job Identification 210808154

• Job Category Predictive Science

• Business Unit Consumer & Community Banking

• Posting Date 11/11/2026, 01:11 AM

• Locations 450 W 33rd St, New York, NY, 10001, US2100 El Camino Real, Palo Alto, CA, 94306, US

• Job Schedule Full time

• Base Pay/Salary New York,NY $223,000.00-$325,000.00; Palo Alto,CA $223,000.00-$325,000.00

Job Description

As an AI/ML Executive Director in our AI for Operations organization, you will lead the creation and operation of a complex, constraint-based optimization and recommendation ecosystem supporting the bank’s operations. You will integrate time-series predictions and demand forecasts with optimization models that pursue global, system-wide business objectives while satisfying interdependent operational constraints. This role combines significant business stakeholder management and communication across executive, product, business, and analytics partners with hands‑on technical leadership. You will own the solution holistically—from business problem formulation and architecture design through data system creation, AI model development, optimization, deployment, and ongoing production operations.

Job Responsibilities

• Lead the design and delivery of a complex constraint-optimization recommendation system that translates time-series predictions and demand forecasts into actionable operational decisioning

• Formulate global, system-wide optimization objectives, decision variables, and hard and soft constraints with business partners; address competing goals, resource and capacity limits, cross-functional dependencies, and forecast uncertainty to deliver feasible recommendations.

• Develop and validate time-series and demand-driven predictive models, accounting for seasonality, changing demand patterns, and uncertainty; integrate forecast outputs into optimization workflows and evaluate both predictive accuracy and downstream decision quality.

• Build and lead a multidisciplinary team of applied AI/ML researchers, optimization specialists, and engineers; provide technical and career guidance while maintaining hands‑on accountability for solution quality and execution.

• Drive significant business stakeholder management across executive leadership and product, business, analytics, data, and engineering partners; translate business needs into technical requirements, align priorities and success measures, and clearly communicate recommendations, trade‑offs, risks, and progress to technical and nontechnical audiences. Collaborate with cross-functional partners including product, data and engineering.

• Own production operation of the prediction and optimization ecosystem, including model and data monitoring, forecast drift detection, constraint‑feasibility checks, retraining, incident resolution, and continuous improvement of reliability and business outcomes.to

• Drive the full product and technical lifecycle, from problem definition, roadmap, and measurable deliverables through experimentation, back testing, scenario analysis, deployment, adoption, and ongoing performance evaluation.

• Serve as the hands‑on technical architect and code contributor for the end‑to‑end ecosystem; design and build scalable data systems, ingestion and transformation pipelines, forecasting services, optimization engines, recommendation interfaces, and production orchestration with appropriate data quality, governance, and observability.

• Contribute to the continuous learning mindset of the organization by bringing in new knowledge, ideas, and perspectives.

Required qualifications, capabilities, and skills:

• PhD in Computer Science in Artificial Intelligence, Operations Research, or a closely related quantitative discipline, with rigorous education in constraint optimization and core AI/ML methods, a strong computer science foundation, and substantial research and industry experience developing and executing complex AI systems and models.

• Outstanding business stakeholder management and written and oral communication skills, with demonstrated ability to influence executive leadership and partners at multiple levels across product, business, and analytics; explain complex technical concepts, negotiate priorities and constraints, and build alignment around measurable outcomes.

• Extensive hands‑on experience developing, deploying, and operating large‑scale AI/ML systems, including time‑series forecasting, demand prediction, and recommendation or decision systems; demonstrated ownership from model development and validation through production execution and ongoing monitoring.

• Deep expertise in mathematical and constraint optimization, including formulating objective functions and interdependent constraints, selecting appropriate solvers and algorithms, and managing feasibility, scalability, and solution‑quality trade‑offs across global business goals.

• Advanced, demonstrable programming skills developed over 10+ years of combined doctoral research and industry experience, with proficiency in more than one programming language.

• Strong computer science background in data structures, algorithms, operating systems, compilers, distributed computing, and databases, with demonstrated ability to architect and create scalable data systems and integrate predictive models, optimization services, and production workflows into a reliable technical ecosystem.

Preferred qualifications, capabilities, and skills:

• Advanced research or specialized doctoral work at the intersection of AI/ML, time‑series forecasting, demand modeling, and constraint optimization, including mixed‑integer, stochastic, robust, or multi‑objective optimization.

• Deep experience with distributed infrastructure, data platforms, and computational methods, including distributed ML and scalable optimization, together with production model lifecycle management and delivery of complex forecasting and decision systems in operational environments.

• Preferred technologies include Python, Spark, Scala, and Java, alongside practical experience with AI/ML frameworks and optimization solvers.

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 (https://careers.jpmorgan.com/us/en/how-we-hire/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.