Research Data Analyst 2

Research Data Analyst

Stanford University Department of Biomedical Data Science has an excellent opportunity available for a candidate interested in single-cell genomics, open science, and big data management as a part of the Lattice team.

Single-cell genomics has led to many recent advancements in our understanding of biological processes, development, and disease. The field continues to see explosive growth in data generation, and simultaneously, AI and ML models are offering increasingly powerful mechanisms to extract insights for the vast amounts of data. As the field continues to accelerate, effective data coordination and standardization become more critical to maximize the value of the data.

The Lattice team aims to accelerate scientific discovery by extending the lifecycle of data generated by the single-cell community. By sharing data in alignment with FAIR principles, they can be readily available for various reuse cases like large-scale data integrations, AI model training, and hypothesis generation. Lattice achieves this, in part, as the Submission Team for CZ CELLxGENE Discover, an open database and visualization platform for single-cell genomic data developed by Biohub. The Lattice team, along with computational biologists and software developers at Biohub, sets requirements for data hosted at CELLxGENE and collaborates with researchers to populate the CELLxGENE data corpus.

Additionally, Lattice team members are stewards for researchers funded directly by Biohub, most notably through their Billion Cells Project initiative. We collaborate with researchers to translate their experimental protocols into standardized metadata, work with industry partners to ensure accurate data processing and delivery, and ultimately, deliver the data to the scientific community.

The Research Data Analyst will join a small team of Ph.D. biologists, computational biologists, and experienced database managers in the GECKO (GEne Curation and KnOwledge) Group, and will work closely with external researchers and software developers. To ensure data are described by sufficient metadata, formatted in an interoperable manner, and error-free, the successful candidate will remain current on single-cell experimental methods and bioinformatics tools through published literature, attending scientific conferences and workshops, and building relationships with researchers in the community. They will distill learnings into schema specifications, quality assurance checks, or other data resource requirements and features that will improve the usability of data to researchers worldwide. We look forward to adding a motivated Research Data Analyst to be a valued contributor towards our mission as a part of this impactful project.

Duties Include

• Collaborate with motivated single-cell researchers to share their data via CELLxGENE
• Develop quality assurance mechanisms for data wranglers to use to ensure data correctness
• Explore how CELLxGENE can expand support to more data types, and design standards around those
• Engage with current and prospective CELLxGENE users at international scientific conferences
• Work with Biohub-funded researchers to help them share standardized metadata and data products
• Update the internal Lattice DB to make data submission, QA, and retrieval more efficient
• Submit requested updates and additions to ontology resources that will then facilitate metadata standards
• Other duties may also be assigned

The expected pay range for this position is $108,002 to $128,138 per annum.

Stanford University provides pay ranges representing its good faith estimate of the salary or hourly wage the university reasonably expects to pay for a position upon hire. 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. At Stanford University, base pay represents only one aspect of the comprehensive rewards package.

The Cardinal at Work website (https://cardinalatwork.stanford.edu/benefits-rewards) provides detailed information on Stanford’s extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.

Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources at stanfordelr@stanford.edu. For all other inquiries, please submit a contact form.

Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

Desired Qualifications

• Bachelor's degree and three years of relevant experience or combination of education and relevant experience.
• Experience in a quantitative discipline such as biostatistics or computational biology.
• Ability to understand experimental procedures described in scientific literature to contextualize the output data.
• Familiarity with genomics, either data generation and/or analysis.
• Working knowledge of Python programming.
• Strong organizational skills
• Communicate effectively and professionally with scientists across academic and industry settings.
• Strong written and oral English communication skills.
• Computer skills, including word processing and spreadsheet applications.
• Excellent writing and analytical skills.
• Ability to prioritize workload.

Education & Experience (required)

• Bachelor's degree and three years of relevant experience or combination of education and relevant experience.
• Experience in a quantitative discipline such as economics, finance, statistics or engineering.

Knowledge, Skills And Abilities (required)

• Substantial experience with MS Office and analytical programs.
• Excellent writing and analytical skills.
• Ability to prioritize workload.

Certifications & Licenses

None

PHYSICAL REQUIREMENTS*:

• Sitting in place at computer for long periods of time with extensive keyboarding/dexterity.
• Occasionally use a telephone.
• Rarely writing by hand.
• 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

Some work may be performed in a laboratory or field setting.

Key skills/competency:

• Research Data Analyst
• Single-cell genomics
• Open science
• Big data management
• Data coordination
• Data standardization
• FAIR principles
• AI and ML models
• Bioinformatics
• Python programming