Bioinformatician I

Benaroya Research Institute•Seattle, WA

1d•$78,890 - $122,280

About The Position

Benaroya Research Institute (BRI) is seeking an outstanding data scientist to join their collaborative bioinformatics group. This team partners closely with bench scientists and clinical researchers to generate insights into immune system function in health and disease. They leverage statistical, computational, machine learning, and AI-assisted approaches to analyze complex, high-dimensional datasets and accelerate scientific discovery. The role involves developing creative approaches at the intersection of data collection, integration, and analysis, working with a range of genomic, cellular, and clinical data types, and adding statistical rigor to the experimental process. The ideal candidate will be enthusiastic about using data science and bioinformatic approaches to further BRI's vision of a healthy immune system for every individual.

Requirements

Strong analytical skills.
Proficiency in a modern programming language used in data science (e.g. R, Python, SAS, Matlab, Scala, Java, C++).
Excellent communication and time management skills.
Ability to work both collaboratively and independently.
Comfortable using modern AI-assisted tools and approaches as part of data analysis, programming, and scientific problem solving.
Interested in continuing to develop AI-assisted skills as the field evolves.
Degree in bioinformatics, biostatistics, or other life science with a strong understanding of the principles of bioinformatics.
0-3 years related experience following graduate studies.

Nice To Haves

Experience with machine learning methods (e.g., clustering, classification, dimensionality reduction).
Experience in the biological sciences, especially immunology.
Experience in bioinformatic analysis of high-throughput “-omics” data.

Responsibilities

Develop creative approaches at the intersection of data collection, integration, and analysis.
Work with a range of genomic, cellular, and clinical data types.
Add statistical rigor to the experimental process.
Use data science and bioinformatic approaches to further the vision of a healthy immune system for every individual.