Senior Data Scientist
Job ID: req1251
Employee Type: exempt full-time
Facility: Rockville: 9605 MedCtrDr
Location: 9605 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.
Our core values of accountability, compassion, collaboration, dedication, integrity, and versatility serve as a guidepost for how we do our work every day in serving the public’s interest.
The Frederick National Laboratory is dedicated to improving
human health through the discovery and innovation in the biomedical sciences,
focusing on cancer, AIDS and emerging infectious diseases.
With leading science and technology, the laboratory performs
basic research, supports clinical trials and drug development, develops and
applies next-generation technologies to solve applied problems while serving as
a national resource of high-tech facilities, while also effectively responding
to emerging health threats.
The Biomedical Informatics and Data Science (BIDS)
directorate works collaboratively and helps to fulfill the mission of Frederick
National Laboratory in the areas of biomedical informatics and data science by
developing and applying world leading data science and computing technologies
to basic and applied biomedical research challenges, supporting critical
operations, developing and delivering national data resources, and employing
leading-edge software and data science to effectively enable and advance
The Strategic and Data Sciences Initiatives group in BIDS
works collaboratively to continue to accelerate cancer research with a focus on
increasingly effective use of data and scalable computing while guiding development
of future computational infrastructure and workforce capabilities needed to
address key cancer research challenges.
- Responsible for the analysis of bioinformatics data through the use of machine learning techniques, computational methods, and cloud resources to facilitate analysis such as next generation sequencing, functional genomics data, drug data, natural language processing, molecular dynamics simulations, and image processing.
- Provides expertise and guidance for data integration and data aggregation across multiple data types and data sources.
- Contributes with educational material and expertise for training initiatives across the program.
- Contributes to
development and testing of data science workflows implemented on High
Performance Computing and Cloud systems.
To be considered for this position, you must minimally meet
the knowledge, skills, and abilities listed below:
- Possession of a B.Sc. from an accredited college or university according to the Council for Higher Education Accreditation in areas related to life science, computer science, data science, or biomedical informatics. (Additional qualifying experience may be substituted for the required education). Foreign degrees must be evaluated for U.S. equivalency.
- 8-10 years of experience working in clinical/bioinformatics projects with a strong background in programming (e.g. Python, R, Perl, bash).
- Working knowledge of bioinformatics methods and data formats (e.g., NGS, medical images, NLP, structural biology, molecular dynamic simulations, etc. ) and experience working with Ph.D. and M.D. researchers.
- Hands-on experience working with various life sciences research data and metadata including proteomics, genomics, image analysis, and clinical data.
- Self-motivated and willing to learn and explore technology.
- Must be able to obtain and
maintain a security clearance.
Candidates with these desired skills will be given preferential consideration:
- PhD preferred with degree in life sciences, computational sciences, or data sciences.
- Experience with application of machine learning / deep learning methods for medical data.
- Experience with cloud environment e.g. AWS, Azure or Google Cloud.
- Knowledge of scientific workflows development (e.g. Snakemake, Nextflow, CWL, etc.)
- Experience with use of containers (e.g., Docker, Singularity, etc.)
- Ability to work with ease in a fast paced, agile environment.
- Self-motivated and result-oriented, able to handle multiple projects efficiently.
- Excellent communication and interpersonal skills.
- Must be a team player.
Equal Opportunity Employer (EOE) | Minority/Female/Disabled/Veteran (M/F/D/V) | Drug Free Workplace (DFW)