Research data scientist (Computational Biologist) at Human Longevity
San Diego, CA, US
Purpose of Job:

The computational biologist will join the research team at HLI and contribute to the innovative research and product offering at Health Nucleus. The successful candidate will design and engineer advanced programs performing mining, analysis and assessment of the most comprehensive human genome, microbiome, metabolone, and clinical data available. This will be achieved by leveraging and assessing the most advanced bioinformatics data gathered for the purpose of healthier aging and overall human wellness study. This is an exceptional opportunity to learn and explore the new dimension of Big Data meets Genomic Science.

Tasks and Responsibilities:

Work with large unstructured and structured data sets
Design and evaluate novel approaches for handling and integrating large internal and external (genomics and EHR) data sets
Apply data-mining, and machine learning techniques for a variety of modeling and relevance problems
Conduct design and code reviews
Prototype, develop and test new algorithms
Interface with Bioinformatics Scientists and Research Scientists
Participate in and drive scientific collaborations and publication efforts
Minimum Qualifications (Must have):

MS or PhD in Computational Biology or Data Science, preferably with a focus on statistical learning, applied statistics, and machine learning. Graduates from other relevant scientific or engineering fields would also be considered.
Programming fluency in Python, R, C/C++ or similar languages, in a Linux environment
Strong system building, problem solving and data structures experience
Demonstrate excellent verbal and written communication skills
Excellent critical and analytical thinking with attention to details
Preferred Qualifications:

PhD degree with a strong publication record
Experience with integrative analysis of large scale genomics and electronic health records data
System building, problem solving and data structures experience
Experience in a fast-paced start-up environment