Computational Scientist - Human Genetics

Software Guidance & Assistance, Inc., (SGA), is searching for a Computational Scientist - Human Genetics for a contract assignment with one of our premier Pharmaceutical clients in South San Francisco, CA .
Responsibilities :
The Human Genetics department at the firm is seeking a highly independent computational scientist with a strong hands-on analytical background in genetic epidemiology, statistical genetics, or computational biology, to develop and apply analytical approaches to integrate and interpret genetic, genomic, and clinical data. We are particularly interested in candidates with skill sets that position them to tackle the integration of multiple sources of human biological data, such as whole genome sequencing and single cell RNA-Seq/ATAC-Seq data, including knowledge of emerging multimodal data integration methods.

• Collaborate with scientists in Human Genetics department to analyze large datasets of genetic, genomic, and clinical data from internal studies (including our clinical trials and high throughput screens), collaborations with academic and industry partners, and public external data sets
• Develop analytical approaches to integrate and interpret these data, delivering insights into disease biology to propel our translational goals
• Implement novel machine learning algorithms to understand associations between imaging and omics data
• Coordinate the intake and preparation of new datasets as they become available for analysis
• Document process, findings, and code
• Present findings to the department and cross-functional collaborators and contribute to publications

Required Skills :

• Extensive experience in large-scale genetic/genomic data analysis including one or more of the following areas of expertise:
  • Understanding of principles of genetic epidemiology
  • Association analysis with array- and sequence-based genetic data (GWAS - genome-wide association studies) on human data
  • Analysis of sequence-based molecular assay data (eg RNA-Seq) including differential expression methods, single-cell sequencing data (eg scRNA-Seq, scATAC-Seq) and/or proteomic data
  • Integration of genetic and molecular data for multimodal analyses
• PhD (or Masters with significant experience) in Statistical Genetics, Computational Biology, Bioinformatics, Genetic Epidemiology, or a related field
• Fluent in R, Python, and shell scripting.
• Experience working with git and high performance computing (e.g. the SLURM scheduling manager)
• Curiosity and desire to learn more about human genetics, bioinformatics, and biology
• Ability to produce high-quality analysis results with minimal supervision. This includes meeting key deadlines and making sensible independent decisions
• Good communication skills and experience working as part of a team

Preferred Skills :

• Some familiarity with C++ will be a plus

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SGA is a technology and resource solutions provider driven to stand out. We are a women-owned business. Our mission: to solve big IT problems with a more personal, boutique approach. Each year, we match consultants like you to more than 1,000 engagements. When we say let's work better together, we mean it. You'll join a diverse team built on these core values: customer service, employee development, and quality and integrity in everything we do. Be yourself, love what you do and find your passion at work. Please find us at .
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