The Staff Scientist 1 will serve as the Technical Team Lead for the database of Genotypes and Phenotypes (dbGaP) Submission System team. The dbGaP was developed to archive and distribute the data and results from studies that have investigated the interaction of genotype and phenotype in Humans. This role includes leading the public release of several scientific software packages that were previously available exclusively on the NIH campus.

The Staff Scientist 1 must have extensive experience of bioinformatic data formats and tools, specifically sequence analysis and genome wide association studies tools and formats. He/She/They will communicate and collaborate with MGVDT and IEB leadership to discuss product priorities and activities and provide strategic recommendations for product development and engagement; provide strategic recommendations to MGVDT leadership for development and engagement opportunities so that researchers may take maximal advantage of NCBI’s sequence content as relevant to their research and/or sequence data analysis needs; provide a product vision and plan and prioritizing feature development for informatics applications supporting searching, browsing, and delivery of NCBI sequence and metadata; coordinates work priorities for a multi-disciplinary team comprised of software developers, data curators, and data analysts; serves as the product ambassador internally and externally, keeping customers and stakeholders informed of product status, sharing knowledge, and answering questions related to the product; connects with, and engages in, collaborations with external entities and institutions informing the development of tools delivering sequence data and metadata; supports MGVDT operational goals by collaborating with members of other program product teams, including managers, subject matter experts (SMEs), product owners, project managers, developers, and others; represents NCBI’s products, standards, and values externally, through participation in working groups, committees, presenting at conferences, webinars or publications; and works in an Agile Framework for product development.

Additional responsibilities include: • Providing support to NLM intramural programs requiring experience in processing techniques, with an emphasis on the lifecycle in a scientific setting. • Managing genomic and biological data focused on the connection of data to biology and medicine and the integration of biological and scientific literature information resources. • Modernizing dbGaP software systems so they are well tested, compliant to policies, more efficient and more user friendly. • Planning projects and sprints and ensuring on schedule delivery of new initiative as well improvements of existing system. • Participating in trans-NLM and/or trans-NIH projects and committees, serving in outreach- associated or staff-training activities and leading workgroups or teams, such as those that design or influence improvements in program policies, processes, or other key activities. • Emphasizing data science and management of large and complex biomedical big data. • Ensuring the security and confidentiality of genetic data through encryption and secure data transfer protocols.

The ideal candidate may or may not be a United States citizen and must have a doctoral degree.

• Ph.D. in Bioinformatics, Computer Science, Engineering, Physics, Computational Biology, or?Applied Mathematics. • Software engineering and maintenance, feature/algorithm design from initial concept to implementation and large-scale testing and analysis, pipeline automation engineering and execution. • Experience developing data and document submission interfaces and processing pipelines. • Experience supporting and documenting large legacy technical applications in use in the genomic data ecosystem. • Proficiency in the Python, C++, Bash, SQL, XML/XSLT. • Demonstrated history of implementing intuitive graphical user interfaces (GUI) for applications. • Strong experience managing software development teams in the Agile Scrum software development cycle. • Experience collaborating with internal and external stakeholders and product teams to translate application business requirements into actionable software development tasks. • Extensive experience identifying and leveraging Cloud based solutions for developing high-performance computing resources (e.g., Hadoop, GCP, Kubernetes, gRPC, microservices). • Collaboration on publications focusing on enhancing the accessibility and utility of genetic data through innovative computational tools. • Exceptional demonstrated written and verbal communication skills.

Desired Competencies:

• Experience working on?document processing systems. • Experience in security and confidentiality of genetic data through encryption and secure data transfer protocols. • Knowledge and experience?of modern software development methodologies (e.g., test driven development). • Working knowledge of?modern software development tools;?including version control (e.g., Git), build management and continuous integration (e.g., TeamCity), and issue tracking (e.g., JIRA). • Experience of automated software testing (writing unit and integration tests).

The successful applicant must have demonstrated the necessary skills and abilities to lead, direct, organize, and coordinate complex research and development projects and will have exceptional technical competence. Candidates must be able to work independently, have excellent communication skills and a proven ability to successfully engage with others to create useful resources to achieve shared objectives.

The IEB is responsible for designing and building NCBI's production software and databases. They: (1) perform applied research in the area of data representation and analysis for molecular biology data, including development of computer based systems for the storage, management, and retrieval of knowledge concerning molecular biology, genetics, and biochemistry; (2) design schema and specifications for representation of sequence genetic and structural information in databases which will serve as national resources; (3) design and develop distributed software systems from the prototype to operational phases which provide researchers with both local and remote computational services; (4) coordinate access to sequence, genetic, structural, and bibliographic databases; (5) establish collaborative informatics research projects with NIH Intramural laboratories as well as extramural academic groups; (6) consult and advise other government agencies and research laboratories on advanced methods of software and database design; and (7) develop and promote standards for databases, data exchange, and biological nomenclature. NCBI performs research in computational biology and creates and maintains information systems and computational tools for the biological research and clinical communities. This involves the organization and enhancement of NCBI’s sequence content and delivery of data, tools, and displays to accelerate research and maximize impact on human health. NCBI programs and activities supported by this position are highly complex, mission-critical, and have national and international impact, as they directly support the mission of NCBI - a greater than $150 million research organization with more than 700 staff.

The position of Staff Scientist 1 is located in IEB’s Medical Genetics & Human Variation Development Team (MGVDT). Medical Genetics and Human Variation (MGV) is a field of study within genetics that focuses on understanding the genetic differences among individuals and populations, as well as the relationship between these variations and health and disease. This field is crucial in identifying the genetic basis of diseases, understanding how genes contribute to health conditions, and developing personalized medicine approaches. This field is at the forefront of efforts to understand complex diseases and develop personalized treatments, combining insights from genetics, molecular biology, and epidemiology.

The MGV program archives and disseminates data on human genetic variation and the associated health information for use by researchers and healthcare providers. In our goal to become the indispensable source for such data, MGV works to deliver intuitively accessible and trustworthy human genetic health information worldwide, through web, cloud, and API products.

The MGVDT provides resources for human genetic variation and phenotypes, to advance the understanding of medical genetics and their clinical applications. NCBI’s variation resources offer human genomic variations, including common and rare SNV, other small- scale variations, large structural variations, and associated frequencies, including Allele Frequency Aggregator (ALFA), a new aggregated frequency source based on data from millions of controlled-access research study subjects. Access through the web, APIs, and FTP downloads where the majority of NCBI data are available for downloading, either directly from the NCBI FTE site or by using software tools to download custom datasets.

Selectees who have completed part or all their education outside of the United States must have their foreign education evaluated by an accredited organization to ensure that the foreign education is equivalent to education received in accredited educational institutions in the United States. We will only accept the completed foreign education evaluation. For more information on foreign education verification, visit the National Association of Credential Evaluation Services (NACES) website. Verification must be received prior to the effective date of the appointment.

DHHS, NIH and NLM are Equal Opportunity Employers

The NIH is dedicated to building a diverse community in its training and employment programs. Applications from women, persons from underrepresented groups, and persons with disabilities are strongly encouraged.

Commitment to Diversity and Equal Employment Opportunity

NIH/NLM encourages the application and nomination of qualified women, minorities, and individuals with disabilities. The U.S. government does not discriminate in employment based on race, color, religion, sex (including sexual orientation, pregnancy, and gender identity), national origin, political affiliation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. NIH/NLM will provide reasonable accommodations to applicants with disabilities as appropriate. If you require reasonable accommodation during any part of the application and hiring process, please notify us.