Bioinformatics Associate 3

Dawar Consulting•South San Francisco, CA

14d•Hybrid

About The Position

We are seeking a highly motivated and skilled Bioinformatician to join our team. The successful candidate will play a critical role in developing, implementing, and maintaining robust bioinformatics pipelines for the analysis of next -generation sequencing (NGS) data. This position requires strong expertise in either Python or R programming for data manipulation, statistical analysis, and visualization, applied to various genomics research projects. You will work closely with molecular biologists, geneticists, and computational scientists to support our ongoing research and operations efforts.

Requirements

Training in Bioinformatics, Computational Biology, Genomics, Genetics, Computer Science, or a related quantitative field.
Proven strong programming skills in either Python or R is essential. (Please specify which language you are most proficient in and provide examples of your work if possible).
Solid understanding of next -generation sequencing (NGS) data types, experimental design, and common bioinformatics analysis workflows.
Experience with biological databases and public data repositories (e.g., NCBI, Ensembl, UCSC Genome Browser, TCGA, GTEx). Familiarity with version control systems (e.g., Git).

Nice To Haves

Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and containerization (e.g., Docker, Singularity).
Proficiency with workflow management systems (e.g., Snakemake, Nextflow, Cromwell/WDL).
Experience with statistical modeling and machine learning techniques applied to biological data.
Knowledge of specific sequencing applications relevant to our research (e.g., single -cell genomics, long -read sequencing, epigenomics).
Experience working in a Linux/Unix environment. Familiarity with high -performance computing (HPC) clusters.

Responsibilities

Pipeline Development: Design, develop, test, and optimize automated bioinformatics pipelines for the processing and analysis of diverse sequencing data.
Data Analysis: Perform advanced statistical and computational analyses of genomics data, including variant calling, differential gene expression, pathway analysis, genomic annotation, and custom analyses tailored to research questions.
Scripting & Programming: Write efficient, well -documented, and reproducible code primarily in Python or R for data cleaning, transformation, integration, and visualization.
Algorithm Implementation: Evaluate, implement, and adapt existing bioinformatics tools and algorithms, as well as contribute to the development of novel methods.
Collaboration: Work collaboratively with wet -lab scientists to understand experimental designs, troubleshoot data quality issues, and interpret biological findings.
Troubleshooting & Optimization: Identify and resolve technical issues within pipelines and analyses, optimize computational efficiency, and ensure data integrity.