Bioinformatics Analyst

Description

Remote work

Top Three Skills:

• Excellent communication skills, Proficiency in Python, Solid understanding of NGS technologies and biological assays

As a Bioinformatics Analyst, you will play a critical role in analyzing large genomic and novel 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 enjoy 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.