We are seeking a detail-oriented and intellectually curious data management specialist to join the Research Support team at the Northwestern University Kellogg School. In this role, you will have the opportunity to help Kellogg's faculty and PhD students obtain unique the datasets they need in order to further their research projects. You will manage a portfolio of approximately 60 commercially licensed datasets, and you will also negotiate the acquisition of about 50 novel research datasets from partner organizations each year. You will work with teammates to develop plans for hosting data and coordinate data deliveries and updates. You will also become a subject matter expert for students and faculty who need guidance in using one of our datasets.

The ideal candidate will bring a combination of technical and soft skills to the job. You will need to communicate very well with academics, vendors, and data donors in order to reach win-win acquisition agreements, and you should be comfortable writing queries in order to understand and explain to others what is going on in a newly acquired dataset. As part of Kellogg Research Support, you will join a diverse team people who are all working to expand the cutting-edge research capabilities of the school. These research problems and techniques are constantly evolving. When you join our team, your role has the potential to grow and evolve too.

Required Qualifications and Competencies

• Completion of a bachelor's degree or higher from an accredited college or university
• Experience with data analysis, report writing, or similar experiences
• Strong critical thinking skills, especially when evaluating datasets for completeness and integrity
• Ability to use at least one statistical programming language - such as R, SQL, Python, or SAS
• Working knowledge of data modeling, information security, and Linux concepts

Preferred Qualifications and Competencies

• Completion of a master's degree or higher in economics, library science, information systems, or a similar field
• Prior experience working with commercial data sources commonly used in business research - such as CRSP, Compustat, Bloomberg, or EDGAR
• Familiarity with digital data repositories - such as Datahub, Github, or Dataverse