Our client leverages machine learning to accelerate drug development and transform clinical trial design. Their cutting-edge research spans multimodal generative modeling, representation learning, and reinforcement learning—applied to extract meaningful insights from complex imaging and omics datasets. Position Title: Bioinformatics Analyst Pay Rate: $40–$52/hr (flexible for exceptional candidates) +Benefits Schedule: 8 AM – 5 PM PST Location: Remote or onsite if local Contract: 12-months (Likely to extend or brought on perm) We are currently seeking a Bioinformatics Analyst to support computational biology initiatives, particularly around the analysis of next-generation sequencing (NGS) data. This role is central to advancing our understanding of immune and stromal cell populations within the tumor microenvironment, with a strong focus on single-cell RNA sequencing (scRNA-seq). Key Responsibilities: • Conduct in-depth analysis of internal and public single-cell RNA-seq and TCR-seq datasets, including large-scale data processing, integration, and interpretation across multiple sources. • Execute end-to-end analysis of various NGS datasets, including bulk RNA-seq, scRNA-seq, and scTCR-seq, to support biological discovery and translational research. • Serve as the lead analyst on NGS projects, performing data preprocessing, normalization, differential expression analysis, pathway enrichment, and delivering insightful visualizations and presentations to cross-functional teams. • Extend and optimize existing analysis pipelines by incorporating custom visualizations and conducting targeted, ad hoc analyses to address specific study questions or project needs. Required Qualifications: 1. PhD graduate in Bioinformatics, Genomics, or Computational Biology. 1. Strong statistical analysis and computational skills, including basic proficiency using Linux-based servers and high level of proficiency with the R programming language and packages such as ggplot2. 1. Relevant experience for dealing with large datasets: batch effect detection and normalization, and confounding and covariate adjustment. 1. Experience organizing and documenting code. 1. Strong communication skills including presenting and interpreting biology focused results especially focused on immunology. 1. Prior experience working with immuno-oncology datasets.