Job Description

All submissions must include:
Candidate's primary programming language (Python or R) at the top of the resume.
No job-to-job resumes; resumes must show tangible accomplishments and clear tenure.
Specific NGS pipelines, data types, and tools the candidate has directly used.
Candidate confirmation that they can commit to 1 day onsite weekly.

Bioinformatician (Level II) Job Description
Working Model: Hybrid South San Francisco (1 day onsite / 4 days remote)
Experience Level: 5 10 years hands-on experience required
Education Requirement: Master's degree required

Position Overview
We are seeking a highly skilled and motivated Bioinformatician (Level II) with 5 10 years of hands-on experience and
a Master's degree in Bioinformatics, Computational Biology, Genomics, Computer Science, or a related quantitative
field.
This individual will lead the development and optimization of bioinformatics pipelines, analyze NGS datasets, and
collaborate closely with cross-functional research teams. The ideal candidate is highly proficient in Python or R, has
deep experience with NGS workflows, and thrives in a fast-paced research environment.

Key Responsibilities
Bioinformatics Pipeline Development
Develop, automate, and maintain robust pipelines for RNA-seq, WGS/WES, scRNA-seq, or other
sequencing datasets.
Optimize workflows for reproducibility, scalability, and performance across HPC or cloud environments.

NGS Data Analysis
Perform advanced computational analyses including:
Variant calling
Differential gene expression
Transcriptomic and epigenomic analysis
Pathway/enrichment analysis
Genomic annotation
Conduct QC for FASTQ, BAM/CRAM, VCF, and related formats.

Programming & Scripting
Write efficient, reproducible, and well-documented code in Python or R.
Build custom tools for data integration, transformation, and visualization.

Tool & Algorithm Implementation
Implement, evaluate, and adapt existing bioinformatics tools and algorithms.
Integrate open-source resources to support project objectives.

Cross-Functional Collaboration
Work closely with wet-lab scientists to interpret data, troubleshoot issues, and align computational analyses
with experimental design.
Communicate complex findings clearly to technical and non-technical audiences.

Troubleshooting & Optimization
Diagnose pipeline failures, data issues, and computational inefficiencies.
Ensure data integrity, workflow reproducibility, and methodological rigor.

Documentation & Reporting
Prepare clear reports, visualizations, and presentations summarizing analysis outcomes.
Maintain precise documentation of workflows, code, and datasets.

Continuous Learning
Stay current with bioinformatics tools, NGS technologies, and computational methods.

Required Qualifications
Master's degree is required (Bioinformatics, Computational Biology, Genomics, Computer Science, or
related quantitative field).
5 10 years of hands-on experience working in bioinformatics or computational genomics.

Demonstrated proficiency in Python or R (candidate must specify their primary language).
Extensive experience analyzing NGS datasets and implementing standard workflows.
Proficiency with key tools, including:
STAR, BWA, Bowtie2, GATK, Samtools, bcftools
DESeq2, EdgeR, Seurat, Scanpy
Experience with public genomic databases (NCBI, Ensembl, UCSC, GTEx, TCGA).
Strong understanding of statistics, experimental design, and computational biology principles.
Proficiency using Git/GitHub for version control.
Excellent communication, problem-solving, and organizational skills.

Preferred Qualifications
Experience with workflow management systems (Nextflow, Snakemake, WDL/Cromwell).
Background in cloud computing (AWS, GCP, Azure) and containerization (Docker, Singularity).
Previous work with HPC clusters.
Experience with specialized sequencing applications such as:
Single-cell assays (scRNA-seq / ATAC-seq)
Long-read sequencing (PacBio, ONT)
Epigenomics assays

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