Location: redwood city, California, United States
- Conduct work in accordance with company standard operating procedures (SOPs), company QA/QC policies, client-specific requirements and applicable regulatory guidelines.
- Assist clients by providing analytical strategies in major therapeutic areas and diseases.
- Independent project development, including but not limited to, ascertainment of client needs, recommendations on statistical methodology, and authoring Statistical Analysis Plans (SAPs).
- Evaluate and incorporate latest analytical approaches (e.g. dimension reduction, machine learning, predictive analytics) addressing precision medicine questions in an industry environment.
- Provide quality control and analysis of a wide spectrum of omics datasets, including DNA-based (e.g. whole genome sequencing, whole exome sequencing, targeted sequencing), RNA-based (e.g. RNA sequencing, microarray), and other biomarker data (e.g. proteomics, metabolomics) along with clinical data collected as part of preclinical studies, clinical trials or based on electronic health records.
- Perform statistical programming in R, SAS, and other appropriate languages and validate work products by internal and/or external team members.
- Interpret findings with scientific and business context, and report in Statistical Analysis Reports, executive summaries, slide presentations as needed.
- Attend on site client visits and present findings as needed.
- Provide guidance to internal team members on statistical methodology, scientific programming, omic and biomarker technologies, and clinical operations as needed.
- Ph.D. REQUIRED. Preferred Degree in: Statistics, Biostatistics, Statistical Genetics, Computational Biology, or Bioinformatics.
- At least 3 years of experience in applied projects is required. Industry specific experience is preferred.
- Demonstrated expertise in the theory and application of biostatistics.
- Knowledge of statistical methodologies and applications in genetics/precision medicine is required.
- Excellent analytical and problem-solving skills.
- Excellent written and verbal communication skills.
- Proven ability to work independently and in a team environment.
- Experience with omic data is required; experience with sequencing data is preferred.
- Experience with public databases (e.g. TCGA, UK Biobank) is preferred.
- Proficiency in R programming is required; proficiency in multiple languages (e.g. SAS, Python) is preferred; experience in Linux/UNIX environment is required.
- Experience with machine learning tools and packages (e.g. caret, mlr, TensorFlow, Keras) is preferred
- Experience with statistical and bioinformatics analysis of multiple biomarker data types (DNA, RNA, protein, etc.) is preferred.
- Experience with linear/nonlinear mixed model tools (nlme, lme4, NONMEM, etc.) is preferred.
- Experience with relational databases (e.g. MySQL) is preferred.
- Qualified candidates must be legally authorized to be employed in the US.
Complete the form below to apply for the (Senior) Genetic Data Scientist - Statistical Geneticist role: