Duties
- Provide leadership to meet organizational strategic goals that advance the use of data science methods and tools for scientific discovery and promoting public health.
- Provide technical expertise and project leadership necessary to advance strategic initiatives in the use and effectiveness of data and knowledge driven methods in the organization.
- Identify strategies and implement approaches to understand and respond to the evolving research data needs of the organization.
- Identify, evaluate and recommend tools, techniques, and methods to increase access to and utility of clinical, biological, and other scientific datasets and knowledgebases…
Additional Qualification Requirements:
You must have at least one-year of specialized experience at or equivalent to the GS-13 level in the Federal service, obtained in either the private or public sector, which includes developing organizational data-related strategies and procedures by partnering with the relevant stakeholders (e.g., researchers, leadership) to build consensus around data standardization, integration, sharing, and security processes that provide reliable/readily available data to make informed decisions. This specialized experience includes the following types of tasks:
- Providing oversight and guidance on the implementation and integration of state-of-the-art technologies and solutions for a scientific research organization.
- Supporting scientific data and knowledge management systems by providing guidance on administration and management functions such as architecture, infrastructure, policy development, technology evaluation, short-and long-term planning, etc.
- Providing guidance on creating and modifying scientific applications using programming languages (e.g., R, Python, SQL, Scala, Java, C/C++, Julia) to facilitate data clean-up, standardization, analysis, and retrieval efforts across an organization.
- Presenting findings to senior-level leadership through data visualization techniques (e.g., interactive dashboards, charts, graphs) using programming (e.g., R, Python, SQL, Scala, Java, C/C++, Julia) or software packages (e.g., MatLab, Tableau).
