Business Modeling – Applied AI ML Executive Director
| Company | JP Morgan Chase |
|---|---|
| Location | Plano, TX, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | PhD |
| Experience Level | Senior, Expert or higher |
Requirements
- PhD in a quantitative field such as operations research, industrial engineering, mathematics, or computer science, with expertise in two or more analytical disciplines such as Linear and non-linear continuous optimization, Integer and MIP programming, Real-time optimization, Stochastic modeling, Statistics, data analysis, and experimental design, and Machine Learning Techniques
- 7+ years of hands-on model development
- 3+ years of management experience
- Demonstrated ability to set clear goals, plan ahead, and deliver against tight timelines and strong analytical, interpretive, and problem-solving skills, with a demonstrated ability to think outside the box
- Outstanding written and oral communication skills to present analytical findings and exercise influence across all levels of the organization
- Strong Python programming skills
Responsibilities
- Provide strategic direction and oversee the performance of the Applied AI Modeling team, ensuring alignment with organizational goals
- Recruit, manage, and mentor top talent, fostering a collaborative environment that encourages innovation and continuous learning across the broader team
- Oversee the creation and implementation of AI and quantitative modeling initiatives across Finance and lead the development of optimization frameworks and implementations for budgeting, pricing, branch location planning, and financial analysis
- Research and implement appropriate algorithms and solution frameworks for a mix of problem types, including non-linear, black-box objective, large scale LP, and MIP
- Identify data anomalies, flawed assumptions, and improper behavior in statistical models, ensuring rigorous investigation and model integrity
- Communicate results across a wide variety of audiences, including business stakeholders, Finance and Technology partners, modeling teams in Risk, and Model Risk and Governance Review
- Perform ad hoc optimization analysis to answer immediate business questions and guide strategic decision-making
Preferred Qualifications
- Banking & Financial Services background or experience preferred
- PhD in Economics
- Experience developing advanced forecasting, AI, or ML models in consumer finance, financial services, tech, or a major retailer
- AWS Certified Machine Learning or Microsoft Certified: Azure AI Fundamentals preferred