The University of Pennsylvania, the largest private employer in Philadelphia, is a world-renowned leader in education, research, and innovation. This historic, Ivy League school consistently ranks among the top 10 universities in the annual U.S. News & World Report survey. Penn has 12 highly-regarded schools that provide opportunities for undergraduate, graduate and continuing education, all influenced by Penn’s distinctive interdisciplinary approach to scholarship and learning. As an employer Penn has been ranked nationally on many occasions with the most recent award from Forbes who named Penn one of America’s Best Large Employers in 2023. Penn offers a unique working environment within the city of Philadelphia. The University is situated on a beautiful urban campus, with easy access to a range of educational, cultural, and recreational activities. With its historical significance and landmarks, lively cultural offerings, and wide variety of atmospheres, Philadelphia is the perfect place to call home for work and play. The University offers a competitive benefits package that includes excellent healthcare and tuition benefits for employees and their families, generous retirement benefits, a wide variety of professional development opportunities, supportive work and family benefits, a wealth of health and wellness programs and resources, and much more. Wharton School Overview Founded in 1881 as the world’s first collegiate business school, the Wharton School of the University of Pennsylvania is shaping the future of business by incubating ideas, driving insights, and creating leaders who change the world. With campuses in both Philadelphia and San Francisco, Wharton has over 850 staff, a faculty population of more than 235 renowned professors, and 5,000 undergraduate, MBA, executive MBA, and doctoral students. Each year 13,000 professionals from around the world advance their careers through Wharton Executive Education’s individual, company-customized, and online programs. More than 104,000 Wharton alumni form a powerful global network of leaders who transform business every day. Wharton is home to a dynamic community of staff, bringing a wide range of skills, experiences, and perspectives. To learn more, visit www.wharton.upenn.edu. The Penn Wharton Budget Model (PWBM) is a non-partisan, research-based initiative that provides analysis to policymakers to assess the effects of policy on budgetary outcomes (government revenues and costs) and various economic variables. PWBM’s work is widely cited and has been influential in many key recent policy discussions, including tax reform, budget reconciliation, immigration, Social Security, health care, infrastructure, pre-K education, paid family leave, universal income, and the federal debt. The PWBM team consists of roughly 30 Ph.D. economists, policy analysts, research analysts, software engineers, and developers. PWBM has a unique model – even relative to other scoring entities – that relies on a workflow between data processing, microsimulation (which utilizes large-scale Monte Carlo simulations), dozens of policy modules (including several tax calculators), and a large-scale stochastic macroeconomic overlapping generations (OLG) lifecycle model. An extensive code base, mostly in Python, underlies this workflow, and the model utilizes cutting-edge economic modeling, data science, machine learning, and cloud computing to project policy impacts. The models are frequently updated to reflect the latest economics and empirical research, and many of them require (large) datasets to calibrate them. PWBM is currently building a model automation pipeline to automate the forecasting process. The Data Engineer will be a member of the software engineering team and work closely with PWBM domain experts – economists, policy analysts, and research analysts – responsible for building and calibrating models using large, publicly and privately available datasets. The Data Engineer will design, build, and maintain the data infrastructure with the software engineering team; establish best practices for data ingestion and storage; and coach domain experts to write maintainable extract-transform-load (ETL) code. The Data Engineer will also contribute their expertise and insights to the model automation project to help make the automation pipeline robust to data changes. Position contingent upon funding.
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Job Type
Full-time
Career Level
Mid Level