Data Scientist III, Cancer Genomics Research Laboratory (CGR)

Job ID: req3484
Employee Type: exempt full-time
Division: Clinical Research Program
Facility: Rockville: 9615 MedCtrDr
Location: 9615 Medical Center Drive, Rockville, MD 20850 USA

The Frederick National Laboratory is a Federally Funded Research and Development Center (FFRDC) sponsored by the National Cancer Institute (NCI) and operated by Leidos Biomedical Research, Inc. The lab addresses some of the most urgent and intractable problems in the biomedical sciences in cancer and AIDS, drug development and first-in-human clinical trials, applications of nanotechnology in medicine, and rapid response to emerging threats of infectious diseases.

Accountability, Compassion, Collaboration, Dedication, Integrity and Versatility; it's the FNL way.

PROGRAMDESCRIPTION
Weare seeking an enthusiastic and driven professional with a passion for data andthe establishment of the principles and procedures to protect that data vialong-term curation while facilitating its usefulness and accessibility for thefurtherment of research by the Cancer Genomics Research Laboratory (CGR) andits collaborators. CGR has a long andstoried history of generating high quality data in support of all areas of bioinformaticsand data analysis which has resulted in large amounts of data that needs curatedand presented for preservation and usability.
CGRinvestigates the contribution of germline and somatic genetic variation tocancer susceptibility and outcomes in support of the NCI's Division of CancerEpidemiology and Genetics (DCEG), the world’s most comprehensive cancerepidemiology research group. CGR is located at the NCI-Shady Grove campusin Gaithersburg, MD and is operated by Leidos Biomedical Research, Inc. We care deeply about discovering the genetic and environmental determinants ofcancer, and new approaches to cancer prevention, through our contributions tothe molecular, genetic, and epidemiologic research of the 70 investigators inDCEG. CGR staff form a large multidisciplinaryteam of members comprised from laboratory staff, informaticists and data analysts,project managers, et cetera all while working in concert with theepidemiologists, biostatisticians, and research scientists within the DCEGintramural research program. The DataScientist III will be responsible for the establishment of the data curation proceduresand methods needed to properly preserve the high-quality data and analyses generatedwithin CGR/DCEG and bring them in line with the FAIR principles (Findable, Accessible,Interoperable, and Reusable). This willinclude the establishment of those procedures for new data generation, as wellas the application of those procedures to key legacy datasets. He/she must demonstrate the personal skills tosuccessfully interface with CGR/DCEG staff to understand the background of the dataand how it is used as well as the scientific and technical know-how to accessand evaluate said data. If you have thedesire for the understanding and preservation of high-quality cancersusceptibility data while making it more FAIR, then come and help enable thatdata to provide additional impact and understanding of cancer genetics.
KEYROLES/RESPONSIBILITIES

• Collaborate with CGR project managers, bioinformaticians, DCEG investigators and data science experts to develop and establish data management procedures and controls for the management and curation of CGR-generated datasets as per the FAIR Principles.
• Establish a set of best practices and list of metadata needed for the archival and long-term curation of CGR/DCEG data.
• Evaluate legacy datasets of CGR to effectively apply established curation procedures and allow for standardization, harmonization, and general usability of these legacy datasets.
• Collaborate with established data storage groups within NCI, NCLBR, and NIH to facilitate the archival and curation of datasets while ensuring proper storage and accessibility of the data is maintained.
• Collaborate closely with DCEG PIs and CGR staff to support and establish a culture in support of the FAIR principles to provide greater data accessibility and usability.
• Coordinate as needed with staff at CGR and DCEG to support posting of publication-associated data to repositories in line with NIH Data Management and Sharing policies.

BASICQUALIFICATIONS

To be considered for this position, you must minimally meet the knowledge, skills, and abilities listed below:

• Possession of a Bachelors’ degree from an accredited college or university (according to CHEA) in computer science, bioinformatics, data management, information management, or related field required.
• Foreign degrees must be evaluated for U.S equivalency.
• In addition to education requirements, a minimum of five (5) years of experience working in a bioinformatics, data management, data engineering, or related role.
• Team-oriented with excellent written and verbal communication skills, organizational skills, and attention to detail; ability to interface with many collaborators across multiple roles including project managers, PIs, and bioinformaticians.
• Demonstrated ability in working with and understanding of genetic and epidemiological datasets and how they are used.
• Proficiency in programming languages, such as Python, R, and SQL.
• Demonstrated experience with a variety of systems, platforms, and environments to help facilitate data assessment and understanding of user data access.
• Familiarity with data repositories and/or database systems such as MySQL, PostgreSQL, MS SQL Server, Oracle
• Familiarity of FAIR principles and related best practices.
• Ability to obtain and maintain a security clearance.

PREFERREDQUALIFICATIONS

Candidates with these desired skills will be given preferential consideration:

• Experience managing Omics datasets
• Experience managing and establishing FAIR based data curation procedures
• Experience harmonizing metadata of large legacy datasets from multiple sources
• Proficiency with shell scripting languages such as bash, zsh, ksh, etc.
• Familiarity with cloud computing environments such as AWS and GCP, and cloud storage services such as AWS S3 and GCP GCS.
• Familiarity with genomic data commons, such as NCI GDC, AnVIL, NHLBI BioData Catalyst data platform.
• Familiarity of Omics data analysis procedures to establish an understanding of how the data is used and what is needed to perform analyses.
• Familiarity with project management tools for documentation and communication (Jira, Teams, Slack, etc.) to document status and activities.
• Familiarity with laboratory management systems.
• Familiarity with differing storage platforms and performance tiers.
• Familiarity with distributed version control and code management systems and protocols such as Git.

Equal Opportunity Employer (EOE) | Minority/Female/Disabled/Veteran (M/F/D/V) | Drug Free Workplace (DFW)
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