How to Apply
A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position, include your salary requirements, and outline skills and experience that directly relate to this position.
ABOUT THE STEPHEN M. ROSS SCHOOL OF BUSINESS
The Stephen M. Ross School of Business at the University of Michigan is a diverse learning community grounded in the principle that business can be an extraordinary vehicle for positive change in today's dynamic global economy. The Ross School of Business mission is to develop leaders who make a positive difference in the world. Through thought and action, members of the Ross community drive change and innovation that improves business and society.
Ross is consistently ranked among the world's leading business schools. Academic degree programs include the BBA, MBA, Part-time MBA (Evening and Weekend formats), Executive MBA, Global MBA, Master of Accounting, Master of Supply Chain Management, Master of Management, and PhD. In addition, the school delivers open-enrollment and custom executive education programs targeting general management, leadership development, and strategic human resource management.
About Ross Research
The Ross School of Business is internationally recognized for its research productivity. The School is currently ranked sixth in the University of Texas at Dallas Top 100 Business School Research Rankings.
Research Computing at the Stephen M. Ross School of Business is a service designed to provide material assistance to RBS Faculty and PhD Students with all aspects of an empirical research project (with the exception of writing/editing aspects). The focus of this position is to help Ross researchers identify data sources and to assist with appropriate methods of extraction, manipulation, and analysis of data to support the achievement of research project deliverables. Knowledge of econometrics/quantitative statistical methodology, and proficiency with a variety of statistical software packages/computer programing languages is essential for this position.
Interact with Faculty and PhD Student on empirical research projects
- Discuss research project concepts
- Assist in finding data resources
- Assist in the creation/debugging of programs to extract/manipulate data from traditional data sets, the internet, and social media platforms
- Assist with statistical modeling and analysis
- Assist with statistical programing/debugging
- Assist with general Linux usage and programming/debugging (tcsh/bash,Perl,Python, etc.)
Manage Research Computing Unit
- Perform routine performance and tracking reports
- Oversee tactical and strategic direction
- Determine economic viability of cloud-based approaches to research computing at Ross, and if viable, develop a strategic plan for the new model
- Develop school-wide solution for collecting and analyzing big data
- Develop and administer research computing annual budget
- Liaison with other Ross/University staff and units that support Ross research
Interact with commercial Data and Software vendors
- Contact vendors for information and pricing
- Coordinate cost sharing among potential users
- Install data and create an access environment
- Build and maintain relationships with the firms from which Research Computing acquires data and software
- Install and update commercial software on the RC Grid
Support the Research Computing Constituent Community
- Meet with faculty and PhD students to gather requirements for the research data and software environment
- Meet with other Research Computing organizations at peer institutions to keep abreast of developments within the field
- Keep up to date with data availability, data usage, and appropriate statistical methodologies.
- Master’s degree in Computer Science, Economics, Statistics or related field and minimum of 2-3 years of computer/research experience or equivalent combination of education and related experience
- Proficiency in econometrics and familiarity with quantitative research methods
- Familiarity with complex data sets such as Compustat, CRSP, and United States Census Data
- Experience with the following:
- Redhat Linux usage (some sysadmin knowledge/experience also helpful)
- High level computing language (C/C++, Fortran, Java, etc…)
- Linux tools (tcsh, bash, awk, sed, perl, python, etc…)
- Statistical Packages (SAS, Stata, Matlab, R/S-Plus, Gauss, SPSS, etc…)
- Windows tools (Word, Excel, Access, etc…)
- Ability to work independently with high efficiency and productivity
- Eagerness to learn (expanding knowledge of CS, Economics & Statistics) and adapt to the unfamiliar
- Excellent communication skills
- Professional demeanor and customer-service oriented manner
- Proven ability to successfully interact with a diverse group of people
- Excellent analytical, creative problem-solving and decision-making skills
- Ability to switch between tasks rapidly and efficiently while meeting established deadlines
- Ability to handle sensitive and confidential information
- PhD in Computer Science, Economics, Finance, Statistics or related field
- Experience with the Wharton WRDS environment (both web- and server-based)
- Experience working in an academic environment
- Experience working with big data, including familiarity with platforms/software such as Hadoop, pig, R, and Forsight
Skills testing may be required.
Physical Demands/Work Environment
- May require ability to work from home, providing a dedicated location for work to be done
- May require work during early mornings, nights, and/or weekends
The statements included in this description are intended to reflect the general nature and level of work assigned to this classification and should not be interpreted as all-inclusive.
U-M EEO/AA Statement
The University of Michigan is an equal opportunity/affirmative action employer.