Research Data Analyst (1 Year Fixed Term/Hybrid)

$66,560 - $97,000/Yr

Stanford University - Stanford, CA

Full-time - Entry Level

Stanford, CA

Educational Services

About the position

The Department of Radiology at Stanford University is seeking a Research Data Analyst 1 for a one-year fixed term position. This role is pivotal in managing, analyzing, and extracting insights from extensive medical imaging datasets. The successful candidate will work within the Integrative Biomedical Imaging Informatics (IBIIS) Division, collaborating closely with the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI). The primary focus will be on assisting with data management and the development of innovative imaging biomarkers derived from various medical imaging modalities. The candidate will be responsible for handling multi-modality datasets, which include biomedical imaging, clinical notes, and categorical variables. The role will require expertise in inverse problems for compressive reconstruction of undersampled medical images, the development of medical image analysis algorithms, and familiarity with language models for parsing clinical notes. A significant portion of the work will involve retrospective data that has already been acquired. The ideal candidate should possess experience with standard programming and data exploration/analysis frameworks, particularly in Python and its common packages such as PyTorch and JAX. Additionally, a solid understanding of software engineering principles is essential for success in this role. Key duties include collecting, managing, and cleaning datasets; employing tools to interpret, analyze, and visualize multivariate relationships in data; creating databases and reports; developing algorithms and statistical models; and performing statistical analyses tailored to data and reporting requirements. The candidate will also be expected to identify and rectify problematic data, suggest solutions, and collaborate with faculty and research staff on data collection and analysis methods. Effective communication with government officials, grant agencies, and industry representatives is also a critical aspect of this position.

Responsibilities

• 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.

Requirements

• Bachelor's degree in computer science, bioengineering, electrical engineering, or other related quantitative fields.
• Experience with programming and data exploration and analysis frameworks (for example, Python, etc).
• Experience in developing software algorithms on local and cloud platforms.
• General understanding of scientific principles.
• Demonstrated performance to use knowledge and skills when needed.
• Demonstrated ability to apply theoretical knowledge of scientific principles to problem solving.
• Ability to maintain detailed records of experiments and outcomes.
• General computer skills and ability to quickly learn and master computer programs, databases, and scientific applications.
• Ability to work under deadlines with general guidance.
• Excellent organizational skills and demonstrated ability to accurately complete detailed work.

Nice-to-haves

• Experience working with medical images and deep learning.
• Experience working with inverse problems.
• Experience working with large language models.

Benefits

• Comprehensive rewards package including health insurance, retirement plans, and paid time off.
• Opportunities for professional development and continued education.
• Flexible work arrangements including hybrid work options.