Research Data Analyst 1
Research Data Analyst 1
Job Number: 81300
Stanford University, Department of Medicine is seeking a Research Data Analyst 1 to Manage and analyze large amounts of information, typically technical or scientific in nature, under the direction of project researchers, investigators, or managers to work within Stanford Center for Biomedical Research.
At the Stanford Center for Biomedical Research (BMIR) we develop cutting-edge ways to acquire, represent, and process information about human health. In order to handle the ever increasing amounts of data in healthcare and biomedical research, our faculty, students, and staff investigate and create novel computational, statistical, organizational, and decision-making methods. Our research advances the state of the art in semantic technology, biostatistics, and the modeling of biomedical systems to benefit clinical and translational research as well as patient care.
- 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.
Computer Science or Informatics:
- Proficiency in programming and software development with a habit for robust unit testing
- Experience working with Python + SQL environment and with R for additional statistical analysis
- Web-based user interface design and human-computer interaction testing experience will be valuable
Statistics and Mathematics:
- Machine learning (supervised and unsupervised) methodology and evaluation including discrimination vs. calibration measures and (hyper) parameter optimization through cross-validation.
- Observational research methods including interpreting multivariate regression, missing data imputation, propensity score matching, and bootstrap simulations.
Biomedical / Healthcare Science:
- Understanding of clinical decision making processes, healthcare quality metrics, financial incentives, and decision support interfaces and pitfalls.
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):
- Substantial experience with MS Office and analytical programs.
- Strong writing and analytical skills.
- Ability to prioritize workload.
- Sitting in place at computer for long periods of time with extensive keyboarding/dexterity.
- Occasionally use a telephone.
- Rarely writing by hand.
- Some work may be performed in a laboratory or field setting.
- 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.
Job Series: Research Data Analyst
Job Code: 4751
Location: School of Medicine, California, United States
To be considered for this position please visit our web site and apply on line at the following link: stanfordcareers.stanford.edu
Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.
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