At Caris Life Sciences, the business problem is to improve the standard of care for patients undergoing treatment for cancer by expanding, testing, and validating a suite of molecular biomarkers.
Requirements
- PhD in Data Science, Computational Biology, Bioinformatics, Engineering, or related scientific field.
- Proficiency in Python.
- Proficiency in data visualization.
- Familiarity with Linux ecosystem, Git, and queries from SQL or related database families.
- Experience with common machine-learning Python libraries such as Sklearn, PyTorch, TensorFlow, Keras, etc.
- Experience with interpretation of clinical health records including Electronic Health Records, insurance claims data, or patient histories
- Experience with bioinformatics pipeline development and genetic file types such as VCF, BAM, FASTQ
Responsibilities
- Work with disease experts to determine the cohort selection, model development, and validation steps that make up a project roadmap for a genetic signature.
- Iteratively develop statistical or machine-learned derived features sets built from Caris genetic sequencing data.
- Communicate the impact and interpretation of predicted clinical outcomes for the targeted disease type.
- Structure queries and organize codebases in a streamlined and reproducible manner.
- Compare novel signatures with baselines derived from the molecular health literature.
- Interface with data engineering and bioinformatics teams to understand the intricacies of underlying datasets.
Other
- Ability to communicate quantifiable results through tables, figures, and plots.
- Proficiency in Microsoft Office Suite, specifically Word, Excel, Outlook, and general working knowledge of Internet for business use.
- Must possess ability to sit and/or stand for long periods of time.
- Job may require after-hours response to emergency issues.
- This position may require periodic travel and some evenings, weekends, and/or holidays.
