Stanford Center for Genomics and Personalized Medicine, situated in the heart of SF Bay Area, has an excellent opportunity available for a motivated Data Analyst to provide bioinformatics analysis support within the Stanford research community. This position is a customer-facing technical role that involves working alongside a small team of professionals, which include Ph.D. scientists and engineers, to process next-generation sequencing data in support of diverse genomics research projects. Your customers will include high profile research labs from across Stanford and other international Universities. The ecosystem at Stanford research includes many academic and commercial partnerships. It is a fast paced and professional work environment. It is a deep learning environment with immense growth potential.
The successful candidate will have deep knowledge of high-throughput sequencing technologies, experience with large genomic datasets, and their computational analysis in order to successfully understand these data.
Excellent communication skills are critical. A significant part of your work will involve interacting with customers, creating documentation and specifications during tool development/deployment, and contribute to wiki, FAQs, video tutorials, and publications.
Computational fluency in a Linux environment are essential as all analysis is in a High Performance Computing cluster environment. The successful candidate must be able to learn to work independently, yet collaborate effectively with co-workers. Previous experience working in an academic environment is a plus. The work will take place in a dynamic environment where workload often change rapidly in response to user demand, so the candidate needs to be good at multi-tasking and managing expectations of multiple stakeholders. The successful candidate will comply with University and government health and safety regulations and policies.
Tasks will include managing bioinformatics pipelines for Next-Generation Sequencing data from various platforms, communicating the sequence data processing results to sample submitters in a helpful and timely fashion, and providing answers to technical questions through 1-on-1 communication and through written documentation. Candidate is expected to troubleshoot poor quality data arising from biological issues or analysis artifacts, propose methods to streamline data analysis, provide curation for omics data and implement QC metrics for data visualization. Candidate is expected to follow best practice guidelines in software development and customer support.