Bioinformatics AnalystAnalyst

Job Title: Bioinformatics Analyst
Location: Remote - South San Francisco, CA 94080
Duration: 12 Months+ (Possibilities of Extension)

Pay Rate: $52.50/hr on w2
 
Position Summary:
As a Bioinformatics Analyst, you will play a critical role in analyzing large genomic and Client NGS assay datasets to support drug discovery programs, with a focus on Cell Therapy therapeutics. Your primary responsibilities include executing, applying, and analyzing sequencing and assay data to identify potential therapeutic candidates. You will prepare data packages and summaries that facilitate cross-team communication and decision-making, while building, maintaining, and optimizing computational pipelines to ensure scalability, reproducibility, and efficiency.
 
About You:
You have a strong background in statistics and software development, with proficiency in Python and experience working with both open-source and custom packages. You follow best practices in code development and enProduct collaborating with a diverse range of engineers and scientists. You are skilled at guiding study design and data interpretation, and capable of translating complex biological questions into quantifiable hypotheses and analyses. You thrive in multidisciplinary teams supporting drug discovery efforts.
 
Key Responsibilities:

• Perform quality control on sequencing and alignment data to ensure accuracy and precision.
• Analyze large genomics datasets to extract meaningful insights related to drug discovery.
• Build, maintain, and optimize bioinformatics pipelines for scalability and reproducibility.
• Support diverse drug programs through computational and statistical analyses.
• Develop and refine statistical models and hypothesis tests to interpret complex datasets.
• Clearly communicate study designs, methodologies, and key findings to interdisciplinary teams, including wet-lab scientists and project stakeholders.
• Contribute to presentations and reports highlighting methods and outcomes.

 
Qualifications:

• Proficiency in Python, with experience applying software development best practices.
• Familiarity with cloud computing environments (e.g., AWS) for large-scale data analysis.
• Experience with Git for version control and reproducibility.
• Solid understanding of NGS technologies and biological assays.
• Strong collaboration skills, especially in advising on study design and avoiding pitfalls in collaboration with wet-lab scientists, engineers, and protein designers.
• Excellent communication skills, capable of translating biological questions into rigorous computational analyses.
• Experience supporting drug discovery programs in a biotech or pharmaceutical setting.
• Prior experience presenting complex computational results to diverse audiences.

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