Senior Data Specialist
Job description
Stanford University is seeking a Data Wrangler 2 for the pharmacogenomics efforts in the Department of Biomedical Data Science. This position works as part of a team of scientists and developers to build and expand the world’s largest collection of pharmacogenomics information and accompanying data analysis pipelines. This person will contribute to the development and testing of pharmacogenomic data analysis software tools and pipelines, interactive web functionality, and scripts for data pre- and post-processing and aid in data curation. They will also help identify and analyze suitable datasets for generating allele, diplotype and phenotype frequencies (such as from biobank data), and exploration of genotype-based drug response phenotypes. The Data Wrangler must have the ability to understand and/or become familiar with genomic dataset file formats, state of the art bioinformatics software tools, the scientific literature focused on pharmacogenomics, and the needs of the pharmacogenomics research, translation and implementation communities.
Duties include:
- Identify and acquire data sets for genomic and/or phenotypic analyses.
- Analyze genomic and/or phenotypic data sets using state of the art bioinformatics tools and software.
- Work with developers and scientific staff to identify, develop and test new features, functionality and user interfaces.
- Support scientific and technical needs of the projects as they arise.
- - Other duties may also be assigned
DESIRED QUALIFICATIONS:
- PhD degree in a scientific field
- In-depth training and knowledge of informatics, genomics and pharmacogenetics
- Proficiency with genomic sequencing and genotyping file formats and informatics tools
- Familiarity with PharmCAT and PharmGKB a plus
- Enjoys writing and public speaking
- Detail-oriented
- Computer skills, including scripting/programming and using bioinformatics tools.
EDUCATION & EXPERIENCE (REQUIRED):
Master's degree in scientific field and three years of relevant experience or combination of relevant experience.
KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):
- Strong analytical skills.
- Ability to learn and utilize relational databases, data integration, and statistics.
- Strong written and oral English communication skills.
- Computer skills, including word processing and spreadsheet applications.
- Ability to understand scientific literature, experimental procedures and their limitations, and current needs of the research community.
PHYSICAL REQUIREMENTS*:
Frequently perform desk based computer tasks, seated work and use light/ fine grasping. Occasionally stand, walk, and write by hand, lift, carry, push pull objects that weigh up to 10 pounds.
- Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.
WORKING CONDITIONS:
- May work extended or non-standard hours based on project or business needs. Occasional local travel may be required.
- Some work may be performed in a laboratory setting.
WORK STANDARDS:
- Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
- Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
- Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide, http://adminguide.stanford.edu.
The expected pay range for this position is $94,000 to $114,000 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs.
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