Principal Statistical Geneticist

Description

Company Summary

Avellino is a global leader in precision medicine.  Our mission is confidently empowering healthcare professionals with personalized patient genetic data to deliver patient care. Combining gold standard scientific methods with artificial intelligence, Avellino enables healthcare professionals to know early, act personally and decide confidently. Our technology targets a range of solutions, from advanced diagnostics to therapeutic, in multiple medical specialties and disease states. 

Position Summary

We are looking for an experienced Principal Statistical Geneticist with strong computational skills and demonstrated experience in the analysis of genetic associations to complex traits with large scale datasets.
 

The successful candidate will work on the development of disease scores to mitigate multiple healthcare diagnostic and therapeutic problems. To enable the diagnosis or therapy at the right time to the right individual.

Requirements

Essential Duties:

• The statistical geneticist will use Avellinos’ extensive database of genotype and phenotype data to develop methods and      implement analysis that address questions around associating risk of developing a disease, progressing, comorbidities, complications, or risk      of therapy failure.
• You will use cutting edge statistical genetic analysis methods to generate insights about human disease and diverse complex traits.
• Integrate and lead hypotheses generation from genetics and diverse datasets by employing sound statistical genetics and      computational biology approaches in a pan-therapeutic manner.
• Bring in datasets from external and internal sources to help develop internal resources for various analytical approaches involving genetics.
• Develop and apply innovative statistical genetics approaches to understand and predict complex disease conditions using multi-dimensional –omics and clinical data.
• Develop working prototypes of inference methods for transfer to production software engineers.
• Work collaboratively within a diverse team of Clinical Scientists, Computational Biologists, and Bioengineers.

Qualifications:

• Ph.D. in Statistical Genetics, Genetic Epidemiology, Quantitative Genetics, Biostatistics, or related area, or equivalent.
• Programming experience using Python notebooks and/or R/Bioconductor in analyzing large data sets in modern cluster and      cloud computing environments.
• Proficiency in biostatistics, linear/non-linear regression models, dimensionality reduction, clustering, and/or bayesian      networks methods
• 3 years’ experience with approaches for marker-trait and gene-trait association (GWAS, PheWAS, TWAS, QTL mapping,      Mendelian randomization, etc), especially as they relate to implications in large multi-ethnic cohorts, and/or polygenic risk score prediction / genomic prediction
• Experience conducting human genetic analyses in admixed populations, including genome-wide and local ancestry analysis.
• Ability to develop, benchmark and apply predictive algorithms to identify novel biomarkers, dissect gene/disease      relationships and generate hypotheses
• Knowledge and expertise with whole genome as well as whole exome sequence analysis
• Exposure to and ability to work with data from UK Biobank, DisGeNet, & FinnGen is a plus
• Ability to manage multiple projects in parallel, communicate clearly and effectively and build open and collaborative      relationships
• Experience with communicating insights and presenting concepts to a diverse audience
• Self-driven and works well in interdisciplinary teams