Senior Scientist, Pathology Data Science

Job Description

The Anatomic Pathology Group at our company's South San Francisco site is seeking a passionate and talented Data Scientist with experience in programming, data science, and tissue-based imaging. The successful candidate will join a dynamic digital pathology team to perform digital pathology analysis to support novel drug and biomarker development, particularly in oncology. Experience with datasets from Akoya Phenocycler and/or Vectra systems, as well as comfort with image analysis commercial software and/or open-source tools is highly desirable.

 Key Responsibilities:

• Analyze, visualize, and summarize molecular data from high-dimensional multiplexing IHC assays

• Perform custom data analyses on large datasets, and generate meaningful data visualizations to stakeholders

• Apply rigorous statistical methods and machine learning algorithms to analyze high-dimensional datasets

• Build end to end data visualization tools for non-programmer that help understand and interpret the complex high-dimensional data

• Develop models from datasets to identify associations for potential biomarker development and for further hypothesis testing

• Employ best reproducible research and data integrity practices to generate reusable analysis frameworks for imaging data

• Assist in the development and validation of digital pathology infrastructure solutions for large file management workflow

• Work proactively and collaboratively across disciplines, including pathologists, machine learning scientists, molecular biologists, protein scientists, bioinformaticians, and software engineers

Qualifications:

Education:

• Ph.D. in Bioinformatics, Biostatistics, Computational Biology, Computer Science, Genetics, Mathematics, Molecular Biology, Statistics or related field and relevant experience listed below

Required Experience and Skills:

• Knowledge and experience in computational analysis for image-based histological or tissue-based assay readouts

• Demonstrated expertise in the application of methods of statistical learning and data mining for the integrative analysis of high-dimensional molecular datasets

• Previous experience with experimental design of biological assays, statistical hypothesis testing, and biological interpretation

• Strong programming skills in writing clean and scalable code with application in imaging (e.g. Python, MATLAB) and statistical analysis (e.g. R)

• Experience with data visualization software such as JMP, and PRISM; data visualization Python packages such as seaborn, matplotlib, etc.

• Demonstrate the ability to learn, be proactive and motivated, and consistently focus on details and execution

• Excellent oral and written communication skills

Preferred Experience and Skills:

• Skilled at integrating results generated from multiple omics data sources, and biological knowledge bases to customize analytical approaches for discovery research

• Experience applying AI / machine learning methods for analysis of image-based biological readouts

• High level of comfort with histology/microanatomy

• Experience with digital pathology image analysis software such as Halo, Visiopharm, QuPath, etc.

• Experience with computational analysis and biological interpretation of diverse large-scale experimental datasets (such as ssRNAseq, WES)

• Experience with good software development practices, collaborative software development, productionizing pipelines, and reproducible research principles

• Experience with version control environments, such as Git

• Experience with high-performance Linux cluster and cloud computing

• Experience working in cross-functional teams and in matrixed environments

#EligibleforERP 

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