Bioinformatics Analyst I/II
Fred Hutchinson Cancer Center is an independent, nonprofit organization providing adult cancer treatment and groundbreaking research focused on cancer and infectious diseases.
Based in Seattle, Fred Hutch is the only National Cancer Institute-designated cancercenter in Washington.

With a track record of global leadership in bone marrow transplantation, HIV/AIDS prevention, immunotherapy and COVID-19 vaccines, Fred Hutch has earned a reputation as one of the world's leading cancer, infectious disease and biomedical research centers.
Fred Hutch operates eight clinical care sites that provide medical oncology, infusion, radiation, proton therapy and related services, and network affiliations with hospitals in five states.
Together, our fully integrated research and clinical care teams seek to discover new cures to the world's deadliest diseases and make life beyond cancer a reality.

The mission of Fred Hutchinson Innovation Lab (FHIL) is to help with adoption and to best leverage rapid technological developments that empower translational research related to cancer immunotherapy.
FHIL serves the Fred Hutch Cancer Center and the Immunotherapy research community, which is a highly dynamic and collaborative environment.

As an integral member of FHIL, the Bioinformatics Analyst I/II provides collaborative and innovative analytic support to advance a broad range of projects mostly related cancer immunotherapy, leveraging single-cell and spatial transcriptomic data to support and empower cutting-edge research.
This position will involve working closely with a broad range of investigators at Fred Hutch and beyond.
The Bioinformatics Analyst will be responsible for working with data from current and newly developed commercial assays, and for construction of analytic datasets sourcing elements from potentially diverse data sources, implementation of exploratory and predictive analyses, visualization of data, and communication and presentation of results.

This specific position will provide programming, analytic, and data-processing support for projects requiring supervised and unsupervised machine learning.
Specific responsibilities include working with scientific investigators, senior data scientists and external collaborators; defining and programming data-processing pipelines for data analysis; conducting both prescribed analytical plans and exploratory data analyses; compiling of statistical analyses and the creation of data visualizations.
This position will report to the FHIL Research Lab Manager and take direction from the FHIL Scientific Director.

A cover letter is preferred upon application that describes your interest in the position and any relevant experience.

Responsibilities
Responsibilities will include a variety of analysis methodologies and data file storage/organizational duties.
The following are typical tasks the successful applicant will perform:

• 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.

Qualifications
Minimum qualifications:

• Bioinformatics Analyst I:
Bachelor's degree in Statistics, Biostatistics, Bioinformatics 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, etc).

• Bioinformatics Analyst II:
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.
Familiarity with commonly used Bioconductor packages, ggplot, tidyverse etc.

Preferred qualifications:

• 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.

• Facility with commonly used Bioconductor packages, ggplot, tidyverse etc.
Ability to generate and customize common data visualizations (PCA plots, volcano plots, Circos plots, etc).

• Excellent written and verbal communication skills are absolutely required.