The Position:

We are seeking a talented and motivated bioinformatics research scientist to join our Data Analysis Team (DAT) for 3-6 months. This position offers a unique opportunity to work with experienced professionals to carry out data analysis and machine learning modeling in the world’s largest database of thyroid cancer patients and their genomic data. These projects will be a critical part of Veracyte’s efforts in building a suite of research products. The ideal candidate is passionate about computational biology, eager to learn, and possesses strong analytical, problem-solving, and story-telling skills.

The objective of this position is to build supervised and unsupervised models to predict different biological and clinical endpoints and define molecularly distinct subtypes. A diverse profile of projects will be available across analyzing gene expression and NGS data.

This is a remote friendly position, with an option to work onsite in our South San Francisco or San Diego office. This is a full time, 3 month consultant position with a possible extension.

KEY RESPONSIBILITIES:

• Analyze existing gene expression data with matched biological endpoint, i.e. mutation status, and build genomic signatures for endpoint prediction.
• Review and synthesize literature on thyroid gene signatures predictive of disease progression and treatment outcome.
• Explore and implement cutting edge machine learning models to further enhance our Afirma offering.
• Assess and optimize existing gene expression models and improve their specificity and sensitivity
• Analyze public gene expression data (i.e. TCGA) to build or validate gene signatures.
• Conduct statistical analysis and survival modelling for the clinical events.
• Visualize finding from the data and summarize them in a clear, cohesive narrative.

Who You Are:

• At least 5 years of experience in oncology bioinformatics, with a proven track record of published work.
• Expertise in R programming and data analysis.
• Hands-on experience with Amazon Web Services (AWS).
• Strong proficiency in feature reduction techniques, as well as both supervised and unsupervised learning algorithms.
• Advanced statistical analysis skills, particularly in model performance evaluation.
• Extensive experience in optimizing machine learning models for improved outcomes.
• Excellent ability to summarize and communicate complex data findings with clarity and precision.
• Exceptional attention to detail, with the ability to work effectively in fast-paced, collaborative environments.
• In-depth knowledge of bioinformatics and the development of genomic signatures.
• Proficient in multi-dimensional data visualization techniques, including Heatmaps, U-MAP, and t-SNE.

RELEVANT EXPERIENCE (preferred but not required):

• Basic knowledge of thyroid cancer genomics
• Good knowledge of SQL

LOCATION:

• This is a remote friendly position in US or Canada.
• On-site office available in South San Francisco or San Diego.
• Final pay will be based on local market and currency.

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