Executive / senior industry position
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South San Francisco
The PHC Data Science Imaging group seeks a talented and motivated Senior Data Scientist to join us in supporting the efforts of the Personalized Healthcare (PHC). To aid in the development of novel imaging biomarkers in PHC and their potential use in clinical drug development, the PHC Imaging Group at Roche is responsible for generating and executing plans to: (1) curate and analyze clinical imaging data from Roche’s late stage (Ph3) clinical trials, and (2) devise plans to gain access to and analyze clinical imaging data from a RWD setting (e.g., health registries, hospital systems, etc.).
The position requires extensive cross functional collaborations working with a diverse team of clinical subject matter experts, data- and imaging scientists, statisticians, and IT staff. Your responsibilities will primarily support image analysis efforts within the group, focusing especially on applying Deep Learning and Machine Learning approaches to projects in oncology, neuroscience, and ophthalmology. In addition to developing and applying novel, data-driven approaches to solving RWD image analysis challenges, the position requires the Imaging Data Scientist to work closely with clinical imaging data management group to deploy, maintain and integrate computational solutions. The job will utilize and build on your experience in scientific/medical imaging, data and image management, application of novel statistical and machine learning approaches to `big data’, software development, and scientific data transfers.
Support and contribute to the development of advanced analytics, computer vision, and computational tools to derive novel imaging based biomarkers
Collaborate with internal imaging- and data scientists and external vendors to derive and validate novel imaging biomarkers in support of clinical drug development and RWD evidence (payer support) generation
Curate/clean/organize large and messy clinical imaging datasets
Identify and support imaging data management solutions within PHC
Continually search for opportunities to automate workflows and streamline processes
In-depth knowledge and coding experience in Python (polyglot in multiple programming languages a plus). Hands-on skills in Data Science packages, for instance Pandas, Scikit-learn, and/or numpy, a must.
Extensive experience with commonly used Deep Learning models (2d/3d CNN, LSTM/GRU, etc), modern DL architectures (Resnet, U-net, etc), and frameworks (Tf, pytorch, keras, etc). Hands-on on other ML algorithms (RF, GBM, etc) a plus.
Familiarity with advances in AI research and related applications in medical imaging, and/or computer vision (eg video).
Technical and organizational skills/experience to lead complex, end-to-end ML/DL/AI projects, including typical project stages such as: data engineering, computing/storage resource budgeting, model training, model selection, model evaluation, and communication with other stakeholders.
Fluent in using scientific computing environment e.g. unix / linux shell in a HPC cluster on premise or in cloud, to accomplish common development tasks (eg. editing, testing, efficient debugging, etc.) Hands-on experience with productivity toolchains (eg JIRA, enterprise git.)
Understand the practical aspect of the mathematical foundation of ML, in particular optimization (first order method eg gradient descent, second order method eg Newton-Raphson, why in DL first order is dominant). Understand the practical aspect of statistics (population vs sample, different sampling techniques, etc)
PhD or MS in relevant quantitative field (CS, EE, Physics, Mathematics, Statistics, etc.), and/or adv. Life Sciences degree with significant computational experience
>3yr post-graduate work-experience in fields such as engineering, research, or product development with responsibilities relevant to position.
Publications in the areas of Deep-/Machine Learning, and/or Statistics a plus.
Solid understanding of medical image data formats (eg DICOM)
Excellent communication skills
Internally motivated with a commitment to accuracy and quality