Translational Informatics Data Senior Scientist - #156581

DNAnexus


Date: 02/23/2021 19:30 PM

City: Mountain View, California

Contract type: Full Time

Work schedule: Full Day

Company Description



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.



Job Description



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.


Description


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 developing computational methods and tools for large scale data analysis  to get insights out of data in support of translational genomics research. The ideal candidate is a computational biologist with success in leading research projects combining next-generation sequencing data with various forms of phenotypic, transcriptomic, metabolomic, and other clinical data. They will have strong programming skills, expertise in designing scalable solutions and experience in genomic data analysis for inferring meaningful insights from large biological datasets. They will be knowledgeable and keenly intuitive about translational research including  techniques for data quality control and data analysis at scale including GWAS, PheWAS, PRS and other multi-omics and machine learning analysis. 


Responsibilities 



  • Develop and apply analytical approaches for large, complex genomic data sets in conjunction with clinical, phenotypic, and multi-omics data
  • Define solutions that meet customer requirements and research goals, working closely with program management and engineering team to drive those solutions through development, testing, and customer validation in an agile environment
  • Conceptualize and develop optimal methods/pipelines and Jupyter Notebooks for a diverse set of genomic data analysis workflows that allow domain scientists and savvy users alike to gain insights from large scale data.
  • Analyze real-world datasets such as UK Biobank to understand the underlying data models and research goals.
  • Research, integrate, test, and validate bioinformatics tools and methods with reproducible, scalable and well-tested code on the DNAnexus Platform.

Requirements



  • Ph.D. in computer science, bioinformatics, computational biology, genetics, or related discipline with a computational emphasis;
  • 3+ years of experience in bioinformatics, biostatistics, genomics, statistical genetics, population genetics, systems biology, and/or translational research in either academic or industry settings
  • Strong programming skills with the ability to develop reusable, well-tested software with advanced level knowledge in Python, R, and bash.
  • Experience with big data analytics technologies including Spark, Hive, and Hadoop, and an understanding of relational database concepts.
  • Experience working with large-scale omics datasets, e.g. ENCODE, 1000 Genomes, ExAC/gnomAD, TCGA.
  • Familiarity 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
  • Understanding of cloud computing and high-performance computing.
  • Excellent leadership qualities, interpersonal skills, and verbal and written communication skills. 
  • Thrives in a fast-paced, team-oriented environment
  • Entrepreneurial “can do” attitude with the ability to find creative, pragmatic solutions


Qualifications



Desired Skills


Below are the skills that are highly desirable, but are not required. DNAnexus will provide the necessary training to qualified candidates:



  • Hands-on experience with data wrangling and understanding of big data ETL processes is a plus
  • Hands-on experience with large scale multi-omics data management is a plus
  • 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.
  • 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
  • Familiarity with integrated tools such as GDC DAVE, cBioPortal, i2b2 tranSMART, Spotfire, UCSC Genome Browser, and Ingenuity Pathway Analysis
  • Knowledge of data file structures (data dictionaries, data files, codings CSV, and others) and their usag


Additional Information



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.



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