The Stanford Center for Narcolepsy treats several hundred narcolepsy patients each year. As a result, our research database contains information on several thousand patients from multiple ethnic groups. The Center for Narcolepsy within the Department of Psychiatry and Behavioral Sciences at Stanford University is seeking a Research Data Analyst 1 (RDA 1) to manage and analyze large amounts of information, typically technical or scientific in nature, under the direction of Dr. Emmanuel Mignot. The goals of the Stanford Center for Narcolepsy are to find the cause of narcolepsy, develop new treatments, and eventually prevent and cure this complex disorder.
Interested candidates should include a copy of their CV and a cover letter with their application.
For more information about the Center for Narcolepsy, please visit: https://med.stanford.edu/narcolepsy.html
Duties include:
- Collect, manage and clean datasets.
- Employ new and existing tools to interpret, analyze, and visualize multivariate relationships in data.
- Create databases and reports, develop algorithms and statistical models, and perform statistical analyses appropriate to data and reporting requirements.
- Use system reports and analyses to identify potentially problematic data, make corrections, and determine root cause for data problems from input errors or inadequate field edits, and suggest possible solutions.
- Develop reports, charts, graphs and tables for use by investigators and for publication and presentation.
- Analyze data processes in documentation.
- Collaborate with faculty and research staff on data collection and analysis methods.
- Provide documentation based on audit and reporting criteria to investigators and research staff.
- Communicate with government officials, grant agencies and industry representatives.
* – Other duties may also be assigned
DESIRED QUALIFICATIONS:
- Master’s degree in Neuroscience, Biomedical Engineering, Bioinformatics, or equivalent practice experience.
- Experience with GWAS, hypothesis testing, fixed and mixed model analysis, with a track record of published work using these methods.
- Experience elaborating comprehensive and user-friendly pipelines, supported by detailed documentation.
- High proficiency in Python, R, and bash, and in libraries such as HIBAG, Metal, Tensorflow/Pytorch.
- Team player and strong communication skills.
EDUCATION & EXPERIENCE (REQUIRED):
- Bachelor’s degree or a combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics or engineering.
KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):
- Ability to process large datasets.
- Capacity to optimize data analysis through parallelization.
- Strong writing and analytical skills.
- Ability to prioritize workload.
CERTIFICATIONS & LICENSES:
- Collaborative Institutional Training Initiative
PHYSICAL REQUIREMENTS*:
- Sitting in place at computer for long periods of time with extensive keyboarding/dexterity.
- Rarely writing by hand.
* – Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.
WORKING CONDITIONS:
- Some work may be performed in a laboratory or field setting.
The expected pay range for this position is $64,480 to $97,000 per annum.
Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.
WORK STANDARDS:
- Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
- Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
- Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University’s Administrative Guide, http://adminguide.stanford.edu.