Lead bioinformatics design, development and validation efforts in assay development for new and on-market products. As part of project core teams, this individual must be responsible for coordinating planning, execution, and delivery within timelines and budget constraints.
Apply leading edge knowledge in bioinformatics, genomics, and assay technologies, to contribute to development of company's concepts and principles and to achieve assay development objectives in creative and effective ways.
Drive development study design and all analysis for assay development effort in collaboration with cross-functional teams.
Develop statistical and machine learning techniques to comprehensively evaluate assay performance and create optimization strategies.
Communicate analysis results, methodologies, and scientific findings to internal teams, external collaborators, and stakeholders.
Develop scalable, production-grade workflows for high-throughput NGS data analysis using AWS and containerized environments.
Facilitate successful production pipeline deployment by working closely with infrastructure and engineering teams
Ensure compliance with regulatory standards (CAP/CLIA, FDA, IVDR) throughout the bioinformatics development lifecycle, including rigorous testing and documentation.
Contribute to regulatory submissions and audits by providing technical documentation and validation reports.
Provide scientific guidance and mentorship to junior bioinformatics team members.
Qualification
REQUIRED EXPERIENCEPhD or MS in bioinformaticsProficiency in machine learningStrong proficiency in Python
Required
REQUIRED EXPERIENCE:
PhD or MS in bioinformatics, computational biology, or an adjacent data science field, such as biostatistics, statistics or computer science.
Proven experience - A minimum of 6 -7 years of experience in bioinformatics analysis, algorithm development, and pipeline implementation.
Thorough understanding of NGS technologies and various methods for library preparation (WGS, enrichment, RNA-Seq, methylation, etc.).
Proficiency in quantitative transcriptomics from NGS or expression microarray data in human disease/biology specifically, such as differential expression, dimension reduction, expression-based classifier development, RNA-based signatures, cell type deconvolution.
Proficiency in machine learning, development of novel bioinformatics methodologies, and algorithms development, including benchmarking of computational methods.
Proven experience developing and deploying bioinformatics workflows in AWS (e.g., EC2, S3, Step Functions, Batch, Lambda, etc.).
Strong proficiency in Python, including experience with testing frameworks and SDLC best practices.
Close collaboration with Quality and Regulatory Affairs team on assay and analysis pipeline development and verification.
Demonstrated record of technical and scientific leadership, ownership, and independent work.
RELEVANT EXPERIENCE (preferred but not required):
Track record of working with wet lab scientists on iterative experiment design, execution, analysis, and interpretation as a tightly integrated team.
