(Senior) Genetic Data Scientist - Statistical Geneticist

Location
Working from Home
Posted
Jul 09, 2021
Ref
75
Required Education
Doctorate/PHD/MD
Position Type
Full time

The Opportunity

Key to insitro’s approach to rethinking drug development is linking in vitro cellular phenotypes with patient phenotypes. As a Statistical Geneticist, you will lead the development of cutting edge statistical approaches and workflows to analyze large-scale human cohorts with genetic and multi-dimensional, multi-modality phenotypic data. These will be obtained from public sources, as well as private datasets generated in-house and obtained through our collaborations. You will use genetic association and other statistical genetics techniques that involve integration of genetic, genomic and clinical data to guide in vitro disease model development. You will also work closely with a cross-functional team of life scientists, bioengineers and machine learning scientists to integrate human level data with our high-throughput in-house in vitro genomic and phenotypic data to identify therapeutic targets and develop drugs that have high efficacy and low toxicity.


You will be joining as the founding team of a biotech startup that has long-term stability due to significant funding, but yet is very much in formation. A lot can change in this early and exciting phase, providing many opportunities for significant impact. You will work closely with a very talented team, learn a broad range of skills, and help shape insitro’s culture, strategic direction, and outcomes. Join us, and help make a difference to patients!


About You

  • Ph.D. in statistics, genetics, computational biology or a related discipline, or equivalent practical experience
  • Demonstrated ability to use and develop cutting edge methods for analyzing human genetic data
  • Hands on experience with genetic association testing (eQTL mapping, GWAS, EWAS, PheWAS, etc.) and/or post-association analysis using summary statistics (fine mapping, colocalization, LD score regression, meta-analysis, etc.)
  • Experience mining modern, large-scale genetic databases (e.g. ExAC/gnomAD, UK Biobank, UK10K, EBI GWAS Catalog, 1KG, etc.)
  • Strong fundamentals in applied multivariate statistics; experience working with statistical models for complex datasets, effectively measuring goodness of fit and estimating confidence
  • Proficiency in working with large-scale datasets in Python; experience with R, C/C++ or other compiled, statically typed languages is a plus
  • Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions
  • Passion for making a difference in the world

Nice to Have

  • Experience working with multi-dimensional phenotypes
  • Experience working with genomic data from different modalities (DNA sequencing, RNA-seq, proteomics, DNA accessibility assays, etc.)
  • Experience integrating genetic studies from diverse populations, including correcting for population structure, ethnicity or differences between genotyping platforms
  • Experience applying quantitative trait loci (QTL) approaches to clinical data, including imaging data
  • Familiarity with cloud computing services (e.g., AWS or GCP) and workflow management tools or batch scheduling systems (e.g. SLURM)
  • Proficiency in Linux environment (including shell/Bash scripting), experience with database languages (e.g., SQL) and experience with version control practices and tools (e.g. Git)

Benefits at insitro

  • Excellent medical, dental, and vision coverage
  • Open vacation policy
  • Team lunches (catered daily)
  • Commuter benefits
  • Paid parental leave
  • This role may be based remotely, if preferred


About insitro

insitro is a drug discovery and development company using machine learning and data generation at scale to transform the way that drugs are discovered and delivered to patients. We rely on human genetic cohorts, human-derived cellular disease models, and high-throughput biology and chemistry to identify coherent patient segments, actionable therapeutic targets, and new or existing chemical matter. The goal is to deliver predictive insights to improve the probability of success and reduce the number of costly dead ends along the R&D journey. The company has established enabling collaborations with Gilead in NASH and Bristol Myers Squibb in ALS and is building a pipeline of wholly owned and partnered medicines leveraging its unique insights on patient biomarkers, targets, and molecules. insitro is located in South San Francisco, CA and has raised over $600M from top tech, biotech, and crossover investors since formation in 2018. For more information on insitro, please visit the company’s website at www.insitro.com.