• Imaging Data Scientist & Data Engineer

    Location US-MA-Boston
    Job Posted Date 2 months ago(8/27/2019 5:49 PM)
    Job ID
    2018-11482
    Category
    IT/Health IT/Informatics
    Type
    full time
    Grade
    24
  • Overview

    Located in Boston and the surrounding communities, Dana-Farber Cancer Institute brings together world renowned clinicians, innovative researchers and dedicated professionals, allies in the common mission of conquering cancer, HIV/AIDS and related diseases. Combining extremely talented people with the best technologies in a genuinely positive environment, we provide compassionate and comprehensive care to patients of all ages; we conduct research that advances treatment; we educate tomorrow's physician/researchers; we reach out to underserved members of our community; and we work with amazing partners, including other Harvard Medical School-affiliated hospitals

     

    The Bioinformatics and Data Science group at the Dana Farber Cancer Institute is seeking an intelligent, hard-working and dynamic individual to join our expanding data science team. The group encompasses expertise in data science, medical imaging, machine learning, natural language processing, ml in production, and research. The successful candidate will have proven experience in leading and executing independently large and complex imaging data science projects, and some experience in the supervision of junior staff. The group is part of the Informatics & Analytics department, that seeks to develop a highly interdisciplinary environment to support the overall mission of the Institute and contribute to maintaining superior cancer care to our pediatric and adult patient population.

    Responsibilities

    We are seeking an energetic and motivated Senior Imaging Data Scientist and Data Engineer for our expanding data science team.

     

    The successful candidate will work on a project that will leverage multi-modal samples from over 100,000+ patients.

     

    The main objectives of the project include: 

    • Integrating and analyzing large collections of medical images (eg: Radiology studies, Pathology cases, etc.)
    • Integrating large collections/datasets into cloud-enabled repositories that can be indexed, linked, and used for research purposes
    • Developing libraries and machine learning tools aimed at preprocessing / analyzing / summarizing such large and multimodal image collection
    • Work with our researchers and clinicians to develop functionalities for predicting outcome / biomarker / disease status / response to therapy, based on recent and historical imaging data.

     

    Key responsibilities of the role: 

    • Design and implement a variety of imaging-oriented data science and data engineering pipelines
    • Meeting and consulting with medical doctors and researchers as required to support plans and solutions
    • Regularly produce reports on project updates for project stakeholders and for other team members
    • Contribute to the positive, inspiring, and result-oriented team environment
    • Deep data science and data engineering skills, at the interface of computer science and statistics

    Qualifications

    • PhD or equivalent experience (evidence of impact in data science applied to real life problems in a research setting) ideally within a clinical research environment
    • 2+ years of relevant experience, preferably post PhD
    • Significant scientific background with prior experience in clinical research 
    • Image analysis experience required (eg: Radiology, Pathology, DICOM, Tissue Microarray, H&E, Microscopy images, etc.) 
    • Data engineering experience required
    • Excellent communication and effective problem-solving skills, track record in serving a variety of diverse customers and projects
    • Ability to work independently, prioritize, and manage students/interns if needed, within an interdisciplinary environment that includes physicians, scientists, engineers, and patient advocates.
    • Google Cloud Platform experience preferred
    • Experienced in data science methodologies and techniques, e.g. hypothesis testing, classification, regression, clustering, feature allocation, deep learning, time-series analysis, network modeling, feature selection/engineering.
    • Version control for analyses and big unstructured data (such as images or free text) experience preferred
    • Prior experience supervising at least 1 person a plus 

    Dana-Farber Cancer Institute is an equal opportunity employer and affirms the right of every qualified applicant to receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, national origin, sexual orientation, genetic information, disability, age, ancestry, military service, protected veteran status, or other groups as protected by law.

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