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Job ID: 202223

Data Analyst- School Of Engineering
Tufts University

Date Posted Dec. 21, 2022
Title Data Analyst- School Of Engineering
University Tufts University
Medford, MA, United States
Application Deadline Open until filled
Position Start Date Available immediately
  • Professional Staff
  • Research/Technical/Laboratory
    Information Technology


The mission of the Center for Applied Brain and Cognitive sciences (CABCS) is to bring together a unique interdisciplinary community of scientists and engineers to advance the state of the art in applied brain and cognitive sciences. The center provides an innovative environment for conducting collaborative applied research focusing on measuring, predicting, and enhancing cognitive capabilities and human system interactions for individuals and teams working in naturalistic high-stakes environments.

What You'll Do

Collects and cleans data and performs data analysis. Applies statistical and machine learning methods to describe, summarize, and interpret data, and communicates results to inform decision making. Prepares statistical summaries and reports to interpret data, communicate results and inform decision-making.     This position is a limited term role, renewable annually, based on performance and budget availability.  

What We're Looking For

Basic Requirements
Knowledge and experience typically acquired by:
• Master’s degree in related field, or Bachelor’s degree with several years related experience
• Experience with data processing, analysis, and visualization software
• Ability to manage databases, construct data files, conduct and supervise data entry, and perform data edits/cleaning
• Experience in data quality control
• Ability to work both independently and collaboratively with team
• Strong writing skills and ability to prepare clear documentation
• Strong analytical skills
• Related software such as Python, MATLAB, Microsoft Excel, SQL, Tableau, SAS, and/or R

Preferred Qualifications 

• Expertise in applying machine learning packages to process and interpret complex, multivariate and time-series data.
• Expertise in applying multivariate statistical models, including generalized estimating equations (GEE), linear mixed effects models (LMM), and LASSO regression.

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