Department of Health and Human Services
National Institutes of Health
National Heart, Lung and Blood Institute
Bethesda, Maryland
Staff Scientist Position
Epidemiology and Community Health Branch
The Epidemiology and Community Health Branch (ECHB), National Heart, Lung and Blood Institute (NHLBI), National Institutes of Health (NIH), is recruiting an accomplished staff scientist to support research in the Epidemiology and Community Health Branch.
The newly created ECH branch focuses on discovering the determinants and understanding the etiology and natural history of HLBS diseases, which can inform new approaches in prediction and prevention of diseases. The Branch deploys multimodality ascertainment and analytical approaches with a unifying focus on the phenotypic expressions of heart, lung, blood and sleep diseases, their occurrence and outcomes in populations and their relationship to aging, multimorbidity and social determinants of health.
The staff scientist will develop and lead independent projects that align with the Branch’s priorities and under the direction of the principal investigator. This role requires possessing and maintaining current knowledge of data science methods and tools to support the development of clinical research protocols, defining the scope and intent of the projects, the data to be used, the analytic approaches and methods, technology resource requirements, timelines and significant milestones, and intended outputs.
Knowledge, skills and experience required
The successful candidate will hold a doctoral degree in epidemiology, statistics, or related quantitative field, and minimum 5 years relevant experience. experience in analyzing and managing data from large, longitudinal epidemiologic studies. The candidate will be skilled in programming with SAS, R, STATA, and/or SQL or similar programming languages, including strong macro skills; have strong analytical skills with the ability to organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy; adept at visual presentation of data, memos, and reports to both technical and non-technical audiences; and have ability to respond to time-sensitive requests independently, work well under pressure, as well as work with large amounts of fragmented data in a fast-paced environment. The candidate will also have excellent interpersonal, organizational and time management skills, as well as excellent verbal and written communication skills.
Specific skills and experience in data science applied to epidemiology include:
• Knowledge of diverse data systems, including survey data, health systems data (administrative and electronic health records), vital records, and non-traditional data sources such as social media and unstructured web-based data.
• Data harvesting and data management to generate analysis-ready datasets.
• Analytical methods including machine learning and programming languages applied to epidemiology and clinical research.
• Knowledge of the theories, principles, and concepts of epidemiology and related health sciences, to formulate hypotheses regarding health status and outcomes, and to analyze and interpret data from epidemiology, clinical, research, and administrative data systems.
• Knowledge of computer systems, cloud technology, and statistical and machine learning applications, to apply modeling and machine learning tools to analyze structured and unstructured health data.
Responsibilities of the staff scientist include but are not limited to:
• Provide technical expertise to develop and maintain data standards and programming for the studies, particularly focusing on data quality and integrity.
• Manage large databases, build the programming infrastructure and tools, and work on the design and development of the data structure for data capture and validation
• QC/QA: develop, test and implement QA/QC procedures for data collected from health surveys, transferred from electronic medical records, and acquired from other sources.
Collaborate with Informatics and Information Technology professionals to do so as needed.
• Guide ECH Branch investigators on optimal use of data sources, on the use of data science tools, methods, and statistical models to collect, link, process, code, classify, and analyze epidemiology, clinical, research, and administrative data.
• Support synthesizing and interpreting the relevant literature and other information
• Participates in developing scalable data models and algorithms that can be applied to various topic areas.
• Supports data interpretation and reporting for projects conducted in the Branch.
Collaborations and consultations
• Consults and collaborates with statistical, data science, artificial intelligence (e.g., machine learning) and informatics and Information Technology professionals in the collection, linkage, processing, coding, classification, and analysis of clinical (electronic health records), research, and administrative health data to store and manage systems that enable analysis of large structured and unstructured datasets.
• Consults with statisticians, computer scientists for studies where extensive analytic methodological support or innovation is required.
Applications will be accepted for 30 days. Selection for this position will be based solely on merit, with no discrimination for non-merit reasons such as race, color, religion, gender, sexual orientation, national origin, political affiliation, marital status, disability, age, or membership or non-membership in an employee organization. NIH encourages the application and nomination of qualified women, minorities and individuals with disabilities. NIH provides reasonable accommodations to applicants with disabilities. If you require reasonable accommodation during any part of the application and hiring process, please notify us. The decision on granting reasonable accommodation will be made on a case-by-case basis. This position is subject to a background investigation. Salary is commensurate with research experience.
Interested individuals should send a cover letter highlighting key qualifications, a current curriculum vitae with complete bibliography, brief summary of research interests and experience, and a list of three publications that provide evidence of relevant skills along with corresponding PDF copies of these publications to:
Ms. Eloise Huneidi Office of Intramural Management, NHLBI
E-mail: eloise.huneidi@nih.gov
3 Center Drive Bethesda, MD 20814
PDF versions of documents sent by electronic mail are strongly preferred. DHHS, NIH, and NHLBI are Equal Opportunity Employers.