Translational Informatics Sr. Scientist - Statistical Genetics - #156593
Date: 02/23/2021 19:30 PM
City: Mountain View, California
Contract type: Full Time
Work schedule: Full Day
DNAnexus is the leading cloud-based SaaS company serving the global life science community. DNAnexus’ health informatics platform serves customers across a spectrum of industries — government, biopharmaceutical, clinical diagnostics, healthcare, and academic research in 33 countries with compliant protection of data, privacy, and intellectual property. The platform provides a secure and collaborative environment where genomics, multi-omics, and real world data can be combined with clinical data at scale, providing new insights that can lead to improved diagnostics, new targeted therapies and better patient care.
DNAnexus xVantage Group is passionate about partnerships and client success. Our partnership culture is as important as the technology we provide our clients. Our mission is to help our clients achieve their research and clinical goals with the DNAnexus solutions and services. Our team includes highly sought after experts including data scientists, bioinformaticians, cloud computing experts, and software engineers.
This is an exciting opportunity to join DNAnexus’ growing team. We are looking for a Translational Informatics Scientist to work with an interdisciplinary team of scientists, engineers, and program managers on DNAnexus Apollo™ translational informatics suite. You will be responsible for designing and developing computational methods and tools for large scale data analysis and visualization in support of translational genomics research for DNAnexus customers. The ideal candidate will be deeply knowledgeable and keenly intuitive about NGS data and leveraging it in biological research in conjunction with clinical/phenotypic and multi-omics data. They will have an extremely strong background in statistics with extensive experience in data analysis for getting valuable insights out of large scale data. They will be familiar with techniques for data quality control, proper handling of missing data, and statistical analyses including GWAS, PheWAS, fine-mapping, Mendelian Randomization, PRS, integrative multi-omics analysis (QTLs) and machine learning tools for genomic data analysis.
- Engage with customers to understand the research and analytics goals for the end users in pharmaceutical and academic research settings
- Define solutions that meet customer requirements and research goals, working closely with program management, data science and engineering teams to drive those solutions through development and customer validation in an agile environment
- Conceptualize and develop optimal methods/pipelines including Jupyter Notebooks and scripts for a diverse set of genomic data analysis workflows that allow customer scientists to gain insights from large scale data.
- Deliver solutions to customers with hands-on training, develop and recommend best practices to end users.
- Ph.D. in Statistical Genetics, Genetic Epidemiology, Bioinformatics, computational biology, computer science or related biotechnology field
- 3+ years of experience in bioinformatics, biostatistics, genomics, statistical genetics, population genetics, systems biology, and/or translational research in either academic or industry settings
- Have a strong understanding and experience working with statistical genetics methods and tools including GWAS (PLINK, HAIL, BOLT-LMM, SAIGE, RVtests, SKAT, METAL), PheWAS (PLATO, PHESANT), Polygenic Risk Score analysis (PRS), Mendelian randomization, fine mapping, pathway analysis
- Deep understanding of the differences in existing statistical tools and methods for translational research data analysis
- Understanding of existing techniques for managing and analyzing genomic, clinical/phenotypic, pharmacokinetic, and other molecular data (transcriptomic, metabolomic, proteomic, microbiome), and the challenges in aggregating datasets for reuse in follow on studies
- Experience working with large-scale omics datasets, e.g. ENCODE, 1000 Genomes, ExAC/gnomAD, TCGA
- Advanced level knowledge of programming languages used for data analysis such as Python, R, and bash with ability to develop reusable, customer-facing Jupyter notebooks and scripts for data analysis
- Strong written and verbal communication and presentation skills. This also requires the ability to effectively communicate complex topics with a diverse audience.
- Thrives in a fast-paced, team-oriented environment
- Entrepreneurial “can do” attitude with the ability to find creative, pragmatic solutions
Below are the skills that are highly desirable, but are not required. DNAnexus will provide the necessary training to qualified candidates:
- Understanding of cloud computing and high-performance computing.
- Familiarity with big data analytics technologies including Spark, Hive, and Hadoop, and an understanding of relational database concepts.
- Familiarity with integrated tools such as GDC DAVE, cBioPortal, i2b2 tranSMART, UCSC Genome Browser, and Ingenuity Pathway Analysis
- Familiarity with commonly used reference and annotation databases such as OMIM, ClinVar, gnomAD, and multi-omic QTL databases such as GTEx, eQTLgen, SPANR, and others
- Hands-on experience with cohort design based on clinical datasets such as the UK Biobank is a plus
Based in Mountain View, California, DNAnexus is experiencing rapid growth and is searching for the best talent to join our team. We recently completed a $100 million financing round to advance our growth globally to further serve leading healthcare and life science organizations. Key investors include Google Ventures, Perceptive Advisors, Northpond Ventures, TPG Biotech, and Foresite Capital.
If you are interested in joining our team, please apply today!
All your information will be kept confidential according to EEO guidelines.