Adjunct Faculty in Artificial Intelligence
Remote
Information
"As a dedicated Data Scientist Lead-Market Risk Quant, you may work from one of our regional offices: San Antonio, TX, Plano, TX, Phoenix, AZ, Tampa, FL, Colorado Springs, CO, Charlotte, NC or work remotely in the continental U.S. with occasional Business travel.
This position will report to the Director - Quantitative Risk Management, Enterprise Market Risk within the second line of defense ERM team. In this role, the Lead Data Scientist will build predictive machine learning (ML) models which will be used to challenge first line capital market assumptions (CMAs) that drive strategic asset allocation decisions. Typical responsibilities will include data gathering / wrangling / exploratory data analysis, feature extraction / engineering, fitting the model to an appropriate ML algorithm, and evaluating model performance. Additionally, this role will be responsible for documentation requirements to aid in internal model validation. The initial focus will be on forecasting interest rates and equity market returns, but that scope may broaden over time.
Company
DePaul University
Requirements
"Required Qualifications:
Minimum requirements include a master’s degree in the discipline, or 18 semester/27 quarter hours of graduate work in the discipline, or an undergraduate degree with a minimum of five years demonstrated relevant professional experience. Exceptions may be considered with approval of the dean.
The candidate must have demonstrated experience in working in teaching in an diverse learning environment.
Special Instructions to Applicants:
The School of Computing offers a MS in Artificial Intelligence degree. At the end of the degree, students will be able to design and implement complex intelligent systems and integrate AI techniques into existing applications and processes. Students take courses in core AI concepts and techniques and explore relevant technical areas including natural language processing, big data systems, computer vision, image processing, robotics, and cybersecurity. We seek instructors with professional experience in machine learning and artificial intelligence who can teach in areas relevant to AI including machine learning, deep learning, natural language processing, reinforcement learning, robotics and computer vision.