Research Data Analyst

Overview

The Neuromuscular Division of Neurology is seeking a Research Data Analyst (RDA) with experience in clinical data management to oversee and analyze research data while assuring operational efficiency and regulatory compliance. The RDA will be responsible for data collection, compilation, statistical analysis, reporting, and overall data management support for research initiatives.

The division is pursuing novel approaches to quantify movement using wearables and video-based technologies, as well as development of new analytical methods for MRI data to characterize disease health for individuals with neuromuscular disease. As disease-modifying treatments become available, we work closely with experts in neurology, physiology, and engineering to advance current clinical practice with data-driven tools.

The successful candidate will serve as a primary data manager for multiple clinical studies, ensuring data integrity, regulatory compliance, and efficient data flow from collection through analysis. A typical week involves writing Python scripts to automate data workflows, building and maintaining REDCap instruments, running data quality checks, and coordinating with clinical staff on data collection protocols. Projects involve working with both pediatric and adult patients with neuromuscular diseases in lab and clinical environments.

There are opportunities for long-term growth within the team with the ability to gain critical skillsets for a career in biomedical informatics and sciences. These studies will be conducted at the Stanford University Medical Center. Interested candidates should include a CV and Cover Letter addressing how your education and experience relates to the position described above.

• Prioritize and extract data from a variety of sources such as notes, survey results, medical reports, and laboratory data, and maintain its accuracy and completeness.
• Design and customize reports based upon data in the database. Oversee and monitor regulatory compliance for utilization of the data.
• Use system reports and analyses to identify potentially problematic data, make corrections, and eliminate root cause for data problems or justify solutions to be implemented by others.
• Create complex charts and databases, perform statistical analyses, and develop graphs and tables for publication and presentation.
• Serve as a resource for non-routine inquiries such as requests for statistics or surveys.
• Other duties may also be assigned

• 1-2 years of relevant work experience in data science, data engineering, or analytics
• Proficiency in Python for data processing, automation, and analysis.
• Experience working with healthcare data, clinical databases, or electronic health records is highly preferred but not required.
• Experience with SQL and relational databases.
• Demonstrated experience integrating data from multiple sources or building data pipelines through coursework, internships, or professional work.
• Intermediate to advanced SQL skills, including experience with complex queries, joins across multiple tables, and database design principles. Experience with healthcare or clinical databases strongly preferred.
• Familiarity with REDCap, Google Cloud Platform, Big Query, or other similar data management environments.
• Experience maintaining data pipelines, ETL processes, or automated reporting workflows.
• Basic to intermediate knowledge of statistical analysis methods and their application.
• Ability to work both independently and as part of a diverse multidisciplinary team in a collaborative manner.
• Ability to determine workload priorities and to set and meet deadlines.
• Initiative with strong problem-solving skills to anticipate and solve problems.
• Good oral and written communication skills to effectively work with and present data to clinicians and researchers.
• Excellent organizational skills and attention to detail in maintaining accurate, retrievable records.

Bachelor's degree in a quantitative discipline such as data science, biostatistics, computer science, statistics, or related field.

• Proficiency in Python for data processing, automation, and analysis.
• Understanding of HIPAA and GCP guidelines.
• Experience with MS Office and analytical programs.
• Strong writing and analytical skills.
• Ability to prioritize workload; efficient utilization of time management.

• Frequently stand, walk, twist, bend, stoop, squat and use fine light/fine grasping.
• Occasionally sit, reach above shoulders, perform desk-based computer tasks, use a telephone and write by hand, lift, carry, push, and pull objects that weigh up to 40 pounds.
• Rarely kneel, crawl, climb ladders, grasp forcefully, sort and file paperwork or parts, rarely lift, carry, push, and pull objects that weigh 40 pounds or more.
• Sitting in place at computer for long periods of time with extensive keyboarding/dexterity.
• Occasionally use a telephone.
• Rarely writing by hand.
• Consistent…