Executive Director, AI/ML — Forecasting, Constraint Optimization, and Recommendation Systems at JPMorgan Chase, New York, NY
Executive Director, AI/ML — Forecasting, Constraint Optimization, and Recommendation Systems at JPMorgan Chase in New York, NY. Est. up to $250k. Apply with swipeandhired.
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. <span style="background-color: rgb(198, 198, 198) !important; color: rgb(51, 51, 51); font-family: "Helvetica Neue", "Helvetica Neue_EmbeddedFont", "Helvetica Neue_MSFontServic