Director of Research Support & Analytics

SSRN; Philadelphia (Philadelphia County); On-site; USD 110,000 - 150,000; Full time

Job summary

Wharton School of the University of Pennsylvania seeks a Director, Research Support to advance analytics for the WRDS community, collaborating with faculty and corporate clients. The role focuses on building research programs, refining tools, and guiding empirical studies using large finance and accounting datasets.

The position requires a Ph.D. in Finance or Accounting, plus hands-on experience with Python/SAS, ML, and big data environments. Travel for trainings and site visits may be involved.

Qualifications

• Ph.D. in Finance or Accounting or ABD with anticipated degree this year.
• Minimum 1 year post-bachelor's experience in research analytics and data tools.
• Experience with Python and/or SAS in big data environments; ML/AI methods.
• Experience conducting empirical research using WRDS datasets (CRSP, Compustat, IBES).

Responsibilities

• Provide high-quality analytics, research programs, applications, and tools to the WRDS Academic Research Community and Corporate Clients.
• Offer consultative guidance on empirical research best practices, troubleshoot data/tool issues, and conduct site trainings to promote effective WRDS use.
• Keep track of evolution of top academic research in finance and accounting to inform signature products and new data sources.
• Construct and enhance data-research products by refining analytics, tools, and applications using WRDS data.
• Evaluate and recommend new datasets based on potential to advance research and WRDS offerings.

Skills

Python

SAS

Machine Learning

Textual Analysis

Empirical Research

Education

Ph.D. in Finance or Accounting

Tools

CRSP

Compustat

IBES

Household-Finance datasets

Job description

Wharton School of the University of Pennsylvania seeks a Director, Research Support to advance analytics for the WRDS community, collaborating with faculty and corporate clients. The role focuses on building research programs, refining tools, and guiding empirical studies using large finance and accounting datasets.

The position requires a Ph.D. in Finance or Accounting, plus hands-on experience with Python/SAS, ML, and big data environments. Travel for trainings and site visits may be involved.