Bioinformatics Analyst I/II

Fred Hutchinson Cancer Center•Seattle, WA

6d•Hybrid

About The Position

Fred Hutchinson Cancer Center is seeking a Bioinformatics Analyst I/II to join the Fred Hutchinson Innovation Lab (FHIL). This role will provide collaborative and innovative analytic support to advance projects related to cancer immunotherapy, leveraging single-cell and spatial transcriptomic data. The analyst will work closely with investigators, senior data scientists, and external collaborators to support cutting-edge research. Responsibilities include working with data from commercial assays, constructing analytic datasets, implementing exploratory and predictive analyses, visualizing data, and presenting results. This position will specifically provide programming, analytic, and data-processing support for projects requiring supervised and unsupervised machine learning. The role involves defining and programming data-processing pipelines, conducting analytical plans, and compiling statistical analyses and data visualizations. The position reports to the FHIL Research Lab Manager and takes direction from the FHIL Scientific Director.

Requirements

Bachelor’s degree in Statistics, Biostatistics, Bioinformatics or equivalent education (for Analyst I).
0-2 years of work experience with bioinformatics in the relevant scientific domain (for Analyst I).
Proficiency in, at least, one modern scripting or programming language (Python, R, etc).
Bachelor’s degree in bioinformatics, computational biology, genetics, or related field with at least three years’ direct experience in computational analysis of large sequence-based molecular data sets (for Analyst II).
Direct experience must include best-practice germline & somatic variant calling from exome capture data, analysis of bulk RNA-seq data with multiple contrasts, analysis of multimodal single-cell profiling data, epigenetic profiling, gene set enrichment, and integration of data across multiple modalities (e.g., epigenetic profiling and RNA-seq) (for Analyst II).
Effective use of shell scripting and significant fluency in R and Python 3 are essential (for Analyst II).
Familiarity with commonly used Bioconductor packages, ggplot, tidyverse etc. (for Analyst II).
Ability to generate and customize common data visualizations (PCA plots, volcano plots, Circos plots, etc) (for Analyst II).
Excellent written and verbal communication skills are absolutely required.
Ability to learn new tools and content quickly and independently.
Strong oral and communication skills.
Ability to work collaboratively with a team of individuals with diverse backgrounds and expertise.
A strong interest in developing reproducible analyses and reports.

Nice To Haves

MS degree in Computational Biology, Computer Science, or Bioinformatics, with at least 3 years direct experience in computational analysis of large sequence-based molecular datasets.
Experience analyzing sequence data with effective use of shell scripting.
Familiarity with version control and other software development best practices.
Experience with workflow manager such as NextFlow.
Record and track analysis processing in GitHub, manage data transfers.
Experience working in and developing cloud computing environments is a plus.
Knowledge of and interest in immunology/molecular biology a plus.

Responsibilities

Analyze large sequence datasets from diverse workflows including bulk RNA-seq, single-cell sequencing, and spatial transcriptomics platforms.
Perform quality control and end-to-end analysis of large sequence datasets from diverse workflows.
Ensure integrity and consistency of primary data, track experimental methods and metadata, define standardized analysis pipelines.
Identify best-practice bioinformatics tools and strategies to meet the needs of proposed projects.
Consult with researchers on sound experimental design.
Review current literature to identify and adopt software and methodologies, making new analysis capabilities available to the Hutch community.
Provide figures and written sections to document methods and results for manuscripts, presentations, and grant applications.
Ability to learn new tools and content quickly and independently (although training will be given for specific types of analysis performed in the lab).
Other duties as assigned.