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Senior Computational Research Consultant

Employer
Kellogg School of Management
Location
Evanston, Illinois
Salary
Competitive
Date posted
Apr 6, 2023
Website
https://www.kellogg.northwestern.edu/research-support/

As a Senior Computational Research Consultant (SCRC), you will draw on a broad set of technological, creative, and problem-solving skills in order to accelerate and facilitate ambitious academic research at Northwestern University's Kellogg School of Management. In addition, you will contribute significantly to initiatives that strengthen the School's capabilities in our focus areas of: novel data collection, scientific computing, text manipulation, large scale data exploration, and computational social science.

In this role, you will work closely with our faculty, understand their research challenges, and then design and implement creative solutions that help them move beyond major obstacles in their research work. For example, you might: write web scraping or crowd sourcing programs to collect a unique dataset; use machine learning algorithms to extract information from text documents; take advantage of cluster computing to accelerate an analysis; cloud-based services to analyze large datasets. You will also provide training to researchers throughout the year on best practices for writing code and managing research data.

You will join a dedicated Research Support team at Kellogg. Clients include Kellogg faculty members and doctoral students with a broad spectrum of academic backgrounds, research interests, and technical backgrounds. As SCRC, you will typically engage multiple clients at a time, and these engagements may last from a few days to several weeks.

Expect to work with bright minds on challenging problems, continually evaluate emerging technologies, and apply new techniques to solve research problems. As these technologies and research questions evolve, so will your role.

Specific Responsibilities:

Support Faculty and Student Research

  • Listen critically and effectively in order to understand our faculty's research needs.
  • Conceive, design, prototype, and implement innovative solutions around the collection, transformation, analysis, and visualization of social science research data.

Community Development and Training

  • Encourage our researchers to adopt innovative new technological tools and methods by developing training materials, guides, and other resources.
  • Provide training and consulting for conducting statistical analyses using standard software and tools.
  • Create and update documentation on resources, tools and data management practices.
  • May mentor and coach junior colleagues and Research Fellows, as needed.

Minimum Qualifications:

  • Advanced degree (M.A. or M.S. minimum, Ph.D preferred) with a research component in any quantitative field.
  • At least 4 years experience in roles that require working with data, performing academic research, and/or writing code.
  • 3-5 years experience using at least two of these standard statistical software packages: Matlab, R, Python, SAS, and/or Stata.
  • 1-2 years experience with Unix/Linux, including scripting.
  • Strong understanding of applied statistics methods, particularly as they apply to computational social sciences: logistic regression, structural equations models, constrained optimization, factor analysis, network graphs, sentiment classification, and machine learning techniques.
  • Ability to organize and document datasets intelligently, and to examine data critically for potential errors or inconsistencies.
  • Ability to work independently and manage time effectively in an environment with unpredictable work-flows.
  • Outstanding communication skills with both technical and non-technical clients.
  • Commitment to continual learning and development.

Preferred Qualifications:

  • Experience writing regular expressions rules or using natural language processing (NLP) algorithms to extract information from poorly structured data sources.
  • Working familiarity with cloud-based data storage and processing options
  • Ability to work efficiently with large datasets using scripting languages and/or statistical software packages (Python, R, SAS or similar).

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