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

JPMorgan Chase & Co.
Palo Alto, CA, United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Compensation
$223,000 - $325,000
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Artificial Intelligence Compilers Computer Simulation Computer Programming Databases Data Control Data Structures Data Systems Distributed Systems Python (Programming Language) Machine Learning
+12 more
Recommender Systems Backtesting Tensorflow Scala (Programming Language) Apache Spark Functional Dependencies Build Management Information Technology Multi-objective Optimization Data Management Machine Learning Operations Programming Languages

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., * 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.

Requirements

  • 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.

Benefits & conditions

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.

About the company

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., 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.

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