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

JPMorgan Chase & Co. • New York, NY

17h • $223,000 - $325,000

About The Position

The Executive Director, AI/ML will lead the creation and production operation of a complex constraint-based optimization and recommendation ecosystem for the bank’s operations. The system integrates time-series predictions and demand forecasts with optimization models to pursue global business objectives while meeting interdependent operational constraints. The role combines executive-level stakeholder management and communication with hands-on technical leadership, owning the solution from business problem formulation and architecture through data systems, AI model development, optimization, deployment, and ongoing production operations.

The role leads a multidisciplinary team of applied AI/ML researchers, optimization specialists, and engineers, while remaining hands-on in architecture and code contribution. It drives the full product and technical lifecycle, including roadmap definition, experimentation, back testing, scenario analysis, deployment, adoption, and continued performance evaluation. Production ownership includes model and data monitoring, forecast-drift detection, feasibility checks, retraining, incident resolution, and ongoing reliability and business-outcome improvement.

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, including the ability to influence executive leadership and partners across product, business, and analytics; explain 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, with ownership from model development and validation through production execution and monitoring.
• Deep expertise in mathematical and constraint optimization, including objective-function and interdependent-constraint formulation, solver and algorithm selection, and management of 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.

Nice To Haves

• 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.
• Practical experience with preferred technologies Python, Spark, Scala, and Java, alongside AI/ML frameworks and optimization solvers.

Responsibilities

• Lead the design and delivery of a constraint-optimization recommendation system that converts time-series predictions and demand forecasts into operational decisions.
• Formulate global optimization objectives, decision variables, and hard and soft constraints with business partners, accounting for competing goals, resource and capacity limits, cross-functional dependencies, and forecast uncertainty.
• Develop and validate time-series and demand-driven predictive models, integrate forecasts into optimization workflows, and assess 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 and maintain accountability for solution quality and execution.
• Manage stakeholders across executive leadership and product, business, analytics, data, and engineering teams; translate needs into technical requirements, align priorities and success measures, and communicate recommendations, trade-offs, risks, and progress.
• Own production operations of the prediction and optimization ecosystem, including model and data monitoring, forecast-drift detection, constraint-feasibility checks, retraining, incident resolution, and continuous improvement.
• Drive the product and technical lifecycle from problem definition, roadmap, and measurable deliverables through experimentation, back testing, scenario analysis, deployment, adoption, and performance evaluation.
• Serve as hands-on technical architect and code contributor; design and build scalable data systems, ingestion and transformation pipelines, forecasting services, optimization engines, recommendation interfaces, and production orchestration with data quality, governance, and observability.
• Contribute new knowledge, ideas, and perspectives to the organization’s continuous-learning mindset.

Benefits

• Competitive total rewards package, including base salary determined by role, experience, skill set, and location.
• Eligible roles may receive commission-based pay and/or discretionary incentive compensation in cash and/or forfeitable equity.
• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support.
• Financial coaching.

What This Job Offers

• Job Type: Full-time
• Career Level: Executive
• Education Level: Ph.D. or professional degree