The National Institute on Aging (NIA), a major research component of the National Institutes of Health (NIH) and the Department of Health and Human Services (DHHS), is seeking exceptional candidates for the position of Chief Data and Analytics Officer within the Division of Behavioral and Social Research (DBSR).
As Chief Data and Analytics Officer, you will lead the Division’s data and analytics efforts, including a range of collaborative data science projects and cooperative agreements conducted with partners across NIA and the NIH. The ideal candidate will have a deep understanding of cloud infrastructure, real-world data, federal data sharing policies, and software as a service and will have a proven track record of designing and executing complex data science programs utilizing social and behavioral data resources, and use of real-world data sources for management of complex surveys and clinical trials.
Key Responsibilities include direction of the DBSR Office of Data Resource and Analytics; developing and managing complex data science programs utilizing social and behavioral data sources and real-world data; seamlessly integrating current IT resources/programs to enable broad data sharing and accelerate aging research; staying up-to-date with the latest developments in data science, cloud infrastructure and software as a service. The incumbent will lead trans-NIH activities such as chairing and facilitating use of NIA/NIH funded data and resources, including advising NIH leadership on CMS and NDI data resources; lead and chair internal NIA working groups such as Artificial Intelligence Working Group and Common Data Elements Working Group. This position involves management of the following programs on behalf of Division of Behavioral and Social Research, NIA, and DHHS:
- AD/ADRD Health Care Collaboratory also known as IMPACT Collaboratory (DBSR activity)
- Understanding the Supply of Professional Dementia Care Providers and Their Decisions (DBSR activity)
- Artificial Intelligence and Technologies Centers Program (NIA-wide activity)
- AD/ADRD Real-World Data (RWD) Platform (NIA-wide activity)
- Lead NIA and NIH activities as it relates to RWD with CMS, NCHS, ASPE (e.g., PCORTF activity)
Required Qualifications: To be eligible for this position, candidates must be a U.S. citizen, or U.S. National. Foreign nationals or legal permanent residents are not eligible for consideration. Candidates must indicate their U.S. citizenship status on their CV or within their email application submission.
In order to qualify for this position, candidates must possess either a doctoral-level degree in, biomedicine or a biological related field, or a master’s level or higher degree in:
- or an emerging or related scientific field.
A social or behavioral science degree and/or a degree in a data science-related field relevant to the health sciences is preferred.
In addition, candidates must have at least one year of experience related to the position, including achievements in one or more of the following areas to demonstrate the individual has received recognition as an expert in the field:
- Demonstrated expertise in developing and managing complex, multicomponent data science programs utilizing social and behavioral data sources and real-world data
- Demonstrated expertise and leadership in clinical trials and data science management or administration
- Demonstrated knowledge and leadership in developing and managing programs involving AI/ML tools, data sharing, common data elements, and data linkage approaches to advance social and behavioral science research
- Knowledge and engagement in management of cloud infrastructure and software as a service at NIH and/or in the larger scientific community
If you are a current Federal Title 5 employee, you must have one year of equivalent experience at the GS-14 level or above.
Application Process: Application packages are to include a CV with bibliography and a statement addressing the qualifications and interest in the position and a vision statement for the organization. Application packages can be submitted via email at NIAJobs@mail.nih.gov, Attention: Jasmine Yeung. All application materials must be received by Wednesday, September 27, 2023. For further information, please contact Jasmine Yeung at NIAJobs@mail.nih.gov or by phone at 301-594-7877.
Benefits: A career with the U.S. Government provides employees with a comprehensive benefits package. As a federal employee, you and your family will have access to a range of benefits that are designed to make your federal career very rewarding. Learn more about federal benefits.
Equal Employment Opportunity: The United States Government does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor. Equal Employment Opportunity (EEO) for federal employees and job applicants.
Standards of Conduct/Financial Disclosure: If selected, you will be required to file an Executive Branch Personnel Public Financial Disclosure Report (OGE-278e and OGE-278-T) in accordance with the Ethics in Government Act of 1978. This report is required prior to employment and on a periodic basis during employment. For information, visit the NIH Ethics website: Public Financial Disclosure Reports (OGE Form 278e and OGE Form 278-T) | ethics (nih.gov)
Foreign Education: This position has an education requirement. You are strongly encouraged to submit a copy of your transcripts (or a list of your courses including titles, credit hours completed and grades). Unofficial transcripts will be accepted in the application package. Official transcripts will be required from all selectees prior to receiving an official offer. Learn more about Foreign Education.
Reasonable Accommodation: You can request a reasonable accommodation at any time during the application or hiring process or while on the job. Requests are considered on a case-by-case basis.