Stanford is a place of discovery, creativity and innovation located in the San Francisco Bay Area on the ancestral land of the Muwekma Ohlone Tribe. Dedicated to our founding mission—benefitting society through research and education—we are working toward a sustainable future, accelerating the impact of research with external partners, catalyzing discoveries about ourselves and our world, and educating students as global citizens. Our main campus, which welcomed its first class in 1891, is now home to 650+ student organizations, 36 varsity athletic teams, 20 libraries, 21 living Nobel laureates, 18 interdisciplinary research institutes, seven schools, and a vibrant arts scene. More than 9,000 graduate students and 7,000 undergraduates pursue studies at Stanford each year. Our financial aid program, one of the most generous in the nation, makes it possible for any admitted undergraduate to attend without taking on student debt.

Stanford University is seeking a Research Data Analyst 1 to manage and analyze large amounts of genomic and molecular profiling datasets with machine learning models in a collaborative setting within a lab and in a consortium setting

Duties include:

Employ new and existing machine learning and statistical tools to model, interpret, analyze, and visualize multivariate relationships in genomic datasets

Create and maintain knowledge graphs, databases and reports, develop algorithms and statistical models, and perform statistical analyses appropriate to data and reporting requirements.

Use system reports and analyses to identify potentially problematic data, make corrections, and determine root cause for data problems from input errors or inadequate field edits, and suggest possible solutions.

Develop reports, charts, graphs and tables for use by investigators and for publication and presentation.

Analyze data processes in documentation.

Collaborate with faculty and research staff on data collection and analysis methods.

Provide documentation based on audit and reporting criteria to investigators and research staff.

Participate in collaborative activities within large genomics consortia such as IGVF

DESIRED QUALIFICATIONS:

Proficiency in machine learning algorithms and statistical analysis techniques

Strong familiarity with implanting pipelines for production-scale machine learning model training and evaluation

Experience with visualizing data and communicating results to a diversity of audiences

Familiarity with basic concepts in cell biology and genomics

Familiarity with common bioinformatics command line tools

Experience with version control systems and software engineering best practices such as code reviews, testing, and documentation

EDUCATION & EXPERIENCE (REQUIRED):

Bachelor's degree or a combination of education and relevant experience. Experience in a quantitative discipline such as Computer science, Statistics, Data Science, Bioinformatics, Computational Biology

KNOWLEDGE, SKILLS AND ABILITIES (REQUIRED):

Strong programming skills in Python

Strong software engineering skills

Strong writing and analytical skills

Ability to prioritize workload.

Ability to collaborate closely with others scientists and researchers from diverse backgrounds

Deep interest in computational genomics