Stanford's Graduate School of Business (GSB) seeks a Research Analytics Scientist to facilitate and accelerate academic research by providing technical expertise and support to researchers, faculty, students, and staff.
Requirements
- Strong programming skills in Python and significant experience with research software written in one or more of R, Stata, Matlab, SAS, Julia, JavaScript.
- Strong and demonstrated experience with scientific coding/scripting, preferably in Python, R, Fortran, C++ and various shells.
- Working knowledge of OpenMP, MPI or other parallel processing approach sufficient to advise on SLURM submissions and basic debugging techniques.
- Proficient in debugging SLURM errors associated with complex jobs and recommending solutions.
- Working knowledge of at least one mainstream ML/AI framework and how to execute efficiently in an advanced computing environment.
- Experience with data processing at scale, and an understanding of which tools are appropriate at which times.
- Experience installing and debugging installations of complex scientific applications and associated dependencies.
Responsibilities
- Formulating concrete technical steps towards their unique goals
- Creating new, unique datasets
- Transforming existing datasets to make them model and analysis ready
- Storing and processing large, complex and variable data sets
- Identifying and bypassing bottlenecks in research computing workflows
- Analyzing and visualizing their data
- Understanding and building upon existing literature
Other
- Master's degree in computer science, data science, statistics, or a related field and 5-8 years of relevant experience, or combination of education and relevant experience in computational methods, tools and systems.
- Demonstrated experience and track record of applying advanced computational methods to solve complex research problems.
- Demonstrated experience with high researcher satisfaction, documented contributions to organizational initiatives and projects.
- Excellent oral and written communications with researchers, peers and management.
- Demonstrated experience in leading research projects to apply data science, machine learning, and other advanced computing techniques to solve complex research problems.
