Who you are:
We are looking for a colleague with extensive experience in analysis of sequencing data to support internal research and partner projects. Ideal candidates will have worked on most phases of analysis starting from alignment and variant calling, to phasing and building imputation panels, to running association and burden tests of rare variants. As most very large sequencing datasets will be compiled from multiple sources, understanding the sequencing technologies and how they relate to QC issues and batch effects will be very important. Ideal candidates will be quantitatively rigorous, and will bring significant experience in analyzing large genomic datasets using the best practices of data analysis.
Our team is very collaborative, and the ability to communicate ideas and results to other scientists is key. The scientific questions we are working on, and the scope of our vision mean that most of the necessary tools and methods have yet to be developed anywhere in the world.
We encourage presentation and publication of research results. The full list of our publications can be seen at research.23andme.com/publications/.
What you’ll do:
Analyze human WGS and/or exome sequencing data and actively identify opportunities for analytical and technological improvements.
Run association and burden tests on rare variants and contribute to development of imputation panels.
Design, implement, benchmark, improve and run sequencing analysis pipelines in AWS.
Work collaboratively with members of the Research, Therapeutics, and Engineering teams to integrate human sequencing data into our research program.
Contribute ideas and expertise to help shape the development of our research platform.
What you’ll bring:
Ph.D. in Genetics, Bioinformatics, Computational Biology or another quantitative field (Biomedical Informatics, Computer Science, Mathematics, Statistics, Physics, etc.).
Ability to solve complex problems individually and as part of a team.
Extensive experience in writing robust code; strong programming skills in Python or R.
Proficiency in managing and analyzing data using AWS pipelines.
Demonstrated fluency with tools and methods for sequencing data analysis (bwa, GATK, Picard, samtools, vcftools, RVTESTS, beagle, GenomicRanges, IGV, etc.).
Hands-on experience working with very large genomic datasets, such as 1000 Genomes Project, TCGA, UK10K, GTEx, TOPMED, or similar.
Excellent verbal and written communication skills.
Apply via the 23andMe website: www.23andme.com/careers/4008391002/