Bioinformatics Analyst I/II at Fred Hutch in Seattle, WA

Summary: Fred Hutchinson Cancer Center is a leading nonprofit organization focused on cancer treatment and research. The Bioinformatics Analyst will work in a collaborative environment, performing specialized data analysis and building custom data pipelines for quality control and end-to-end analysis of large datasets related to cancer immunotherapy. Responsibilities: - Implement, apply, and evaluate tools to process, integrate, batch-correct and visualize genomics datasets (single-cell RNA-seq, Bulk RNA-seq, CITE-seq), multiparametric flow cytometry datasets, multiplexed cytokine/protein datasets - Interpret the data and explain the results in research discussions with experimental collaborators - Perform quality control and end-to-end analysis of large sequence datasets from diverse workflows - Identify best-practice bioinformatics tools and strategies to meet the needs of proposed projects - Provide figures and written sections describing methods and results for manuscripts, presentations, and grant applications - Ensure integrity and consistency of primary data, track experimental methods and metadata, define standardized analysis pipelines - 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 Required Qualifications: - BS degree in Biology, Statistics, Computer Science or equivalent education - 0-2 years of work experience with bioinformatics in the relevant scientific domain - Proficiency in, at least, one modern scripting or programming language (Python, R, Node, or C++) - 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 - 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) - Effective use of shell scripting and significant fluency in R and Python 3 are essential - Facility with commonly used Bioconductor packages, ggplot, tidyverse etc - Ability to generate and customize common data visualizations (PCA plots, volcano plots, Circos plots, etc) Preferred Qualifications: - Spatial transcriptomic knowledge or experience, preferably 10x Xenium - Experience with R and statistical analysis - Knowledge of bulk and single cell RNA-seq datasets and analysis methods - Familiarity with cancer immunotherapy research or related biological domains - Experience with data pipeline development and workflow management - Proficiency with Linux/Unix shell scripting (e.g., bash) - Familiarity with cloud servers or high-performance computing resources - Ability to generate and customize visualizations - Strong organizational skills, including the ability to manage and prioritize multiple competing tasks - Good communication skills and an interest in learning - Ability to work independently and in a team - Scientific curiosity Required Skills: Bioinformatics, Data analysis, Python, R Important Skills: Scripting, Data visualization, Genomics datasets, Linux/Unix Nice-to-Have Skills: Scientific curiosity, Communication skills, Organizational skills, Teamwork Benefits: Medical/vision, Dental, Flexible spending accounts, Life, Disability, Retirement, Family life support, Employee assistance program, Onsite health clinic, Tuition reimbursement, Paid vacation (12-22 days per year), Paid sick leave (12-25 days per year), Paid holidays (13 days per year), Paid parental leave (up to 4 weeks)