Bioinformatics Scientist IV

Duties:

• Design, implement, and deploy NGS data analysis workflows for data processing, visualization, integration, and mining to support therapeutic target identification and disease biomarker discovery.
• Perform omics data analysis and interpret genomic data sets (e.g., bulk RNA-seq, scRNA-seq, ATAC-Seq, spatial RNA-Seq).
• Utilize contemporary data visualization methods (e.g., R Shiny, D3).
• Analyze diverse multi-omics datasets to find drug discovery targets relevant to immune diseases.
• Conduct data mining using internal, collaborative, and public databases to assist in the characterization of immune diseases.
• Select and benchmark methods and tools; perform appropriate QC measures.
• Apply and develop innovative analysis approaches when standard methods are not sufficient.
• Interpret and present analysis results to coworkers and collaborators.
• Stay updated with relevant scientific literature for optimal methods and emerging practices.
• Communicate work effectively orally and in writing; contribute to writing protocols, procedures, and technical reports.
• Automate processing, results reporting, and delivery.
• Report and treat data with high integrity and ethics.
• Comply with applicable regulations and maintain proper records in accordance with SOPs and policies.

Required Skills:

• Strong scientific understanding and experience in bioinformatics within a pharmaceutical research environment.
• Experience in analyzing NGS, functional genomics, statistics for big data analysis, or multi-omics data integration.
• Knowledge of existing bioinformatics databases and file formats.
• Understanding of computational methods for NGS analysis and usage of public data resources.
• Proficient in programming languages (e.g., R, Python, Shiny, UNIX/Linux, UNIX bash shell scripting, Nextflow), statistical software, cloud computing, visualization tools, and relevant R/Bioconductor packages.
• Ability to produce well-designed and documented code; familiarity with code repositories like GitHub.

Desired Skills:

• Experience accessing LLMs through APIs (e.g., OpenAI API, LangChain).
• Experience with web app development (specifically Streamlit or Shiny).
• Familiarity with computational biology tools and collaboration with computational biologists.
• Strong troubleshooting skills, both individually and as part of a team.
• Excellent oral and written communication skills.

Education:

• Master’s degree from an accredited institution with 1+ years of experience in a related scientific discipline (Computer Science, Genomics, Biostatistics, or Bioinformatics preferred) OR
• Bachelor’s degree from an accredited institution with 7+ years of experience in a STEM discipline.