Stanford University's Cardiothoracic Department is seeking a highly skilled and motivated researcher to join our team as a Research Data Analyst 1. In this role, you will be responsible for managing and analyzing large amounts of health information with the goal of improving patient care and management.
As a researcher, you will work closely with the department's surgeons, physicians, and researchers to develop and implement advanced data analysis and modeling techniques. You will be responsible for creating and implementing machine learning algorithms that can predict patient outcomes and improve clinical decision-making. You will also be responsible for designing and implementing new data collection methods to improve the accuracy and quality of the data.
To be successful in this role, you should have a strong background in machine learning, data analysis, and statistics. You should also have experience working with large and complex data sets, as well as the ability to develop and implement machine learning models in Python, R, or other programming languages. Additionally, experience with medical data and electronic health records is highly desirable.
- 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.
- Strong foundation in computer science and mathematics, including data structures, algorithms, linear algebra, calculus, and probability theory.
- Expertise in data processing and ETL (Extract, Transform, Load) pipelines, including data integration, data quality, data normalization, and data transformation.
- Proficiency in programming languages such as Python.
- Strong knowledge of machine learning algorithms and models, including deep learning, natural language processing, computer vision, and recommendation systems.
- Familiarity with data visualization and reporting tools such as matplotlib.
- Excellent communication and collaboration skills to work effectively with cross-functional teams, including physicians, and software engineers.
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.