Description

Practice Professor of Economics / Executive Director, Master of Applied Economics and Data Science


Location: Philadelphia, PA
Open Date: May 16, 2025
Deadline:

The University of Pennsylvania (Penn) invites applications for a dynamic and experienced leader to serve as the inaugural Executive Director for the newly launched Master of Applied Economics and Data Science (MEDS) program, housed within the College of Liberal and Professional Studies (LPS). This full-time, non-tenure-track position will be held by a Practice Professor to be appointed in the Department of Economics in the School of Arts and Sciences. It is ideal for an individual with a strong academic, industry, and/or policy background in economics and data science.

Position Overview

The Executive Director will provide oversight to the MEDS program, helping to guide the curriculum, mentoring students, and fostering collaborative partnerships between academia and industry. The objective of the program is to foster students' knowledge and skills in three primary areas: developing and implementing economic models for decision making, extracting information from data using state-of-the-art econometric and machine learning techniques, and acquiring proficiency in relevant software. The successful candidate will be skilled in economics or data science (preferably both), with academic credentials and a proven track record of integrating research and practice. The position is for three years and is renewable based on successful review.

Key Responsibilities

Leading the development, implementation, and continual improvement of the MEDS program in collaboration with the MEDS Faculty Director (a tenured Professor of Economics who provides high-level guidance and development, particularly regarding the curriculum), the MEDS faculty advisory committee (composed of several tenured Professors of Economics who offer advice and serve as a sounding board), and LPS.

Administering the MEDS program, including student recruitment and admissions, advising, and academic support.

Teaching two semester-long courses per academic year in the MEDS program.

Mentoring students and providing advice on capstone research projects, facilitating their professional development as future leaders in the field.

Fostering relationships with the industry, policy, and non-profit communities to ensure that the MEDS program remains responsive to their needs.

Contributing to the MEDS research environment on topics related to economics, econometrics, data science, and/or machine learning, via a combination of publications, presentations, and participation in Departmental events.


Qualifications
A PhD in Economics, Data Science, or a closely related field (required).

Teaching experience in an academic or similar setting (strongly preferred).

Professional experience in applying/managing economic modeling and/or data science in industry or policy settings, as well as research experience in applied economics and/or data science.

Ability to work collaboratively with a range of stakeholders, including academics and university administrators.

Demonstrated managerial and leadership skills.


Application Instructions
Interested candidates should submit the following to apply.interfolio.com/167902

A cover letter outlining qualifications in relation to the goals of the MEDS program.

A detailed curriculum vitae (CV).

A statement of research interests related to economics and data science.

A statement summarizing past teaching experience and copies of teaching evaluations if available.

Contact information for three references.

Review of applications will begin immediately and continue until the position is filled.

Please use lps@sas.upenn.edu for inquiries.


To apply, visit https://apply.interfolio.com/167902

Equal Employment Opportunity Statement

The University of Pennsylvania is an equal opportunity employer. Candidates are considered for employment without regard to race, color, sex, sexual orientation, religion, creed, national origin (including shared ancestry or ethnic characteristics), citizenship status, age, disability, veteran status or any class protected under applicable federal, state, or local law.










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