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    Data Scientist I/II - Seattle, United States - Fred Hutchinson Cancer Center

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    Description
    Overview

    Fred Hutchinson Cancer Center is an independent, nonprofit organization providing adult cancer treatment and groundbreaking research focused on cancer and infectious diseases. Based in Seattle, Fred Hutch is the only National Cancer Institute-designated cancer center in Washington.

    With a track record of global leadership in bone marrow transplantation, HIV/AIDS prevention, immunotherapy and COVID-19 vaccines, Fred Hutch has earned a reputation as one of the world's leading cancer, infectious disease and biomedical research centers. Fred Hutch operates eight clinical care sites that provide medical oncology, infusion, radiation, proton therapy and related services, and network affiliations with hospitals in five states. Together, our fully integrated research and clinical care teams seek to discover new cures to the world's deadliest diseases and make life beyond cancer a reality.

    At Fred Hutch we value collaboration, compassion, determination, excellence, innovation, integrity and respect. These values are grounded in and expressed through the principles of diversity, equity and inclusion. Our mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us stronger. We seek employees who bring different and innovative ways of seeing the world and solving problems. Fred Hutch is in pursuit of becoming an anti-racist organization. We are committed to ensuring that all candidates hired share our commitment to diversity, anti-racism and inclusion.

    The mission of Fred Hutchinson Innovation Lab (FHIL) is to help with adoption and to best leverage rapid technological developments that empower translational research related to cancer immunotherapy. FHIL serves Fred Hutch Cancer Center and the Immunotherapy research community, which is a highly dynamic and collaborative environment.

    As an integral member of FHIL, the Data Scientist provides collaborative and innovative analytic support to advance a broad range of projects mostly related cancer immunotherapy, leveraging single-cell and spatial transcriptomic data to support and empower cutting-edge research. This position will involve working closely with a broad range of investigators at Fred Hutch and beyond. The Data Scientist will be responsible for working with data from current and newly developed commercial assays, and for construction of analytic datasets sourcing elements from potentially diverse data sources, implementation of exploratory and predictive analyses, visualization of data, and communication and presentation of results.

    This specific position will provide programming, analytic, and data-processing support for projects requiring supervised and unsupervised machine learning. Specific responsibilities include working with scientific investigators, senior data scientists and external collaborators; defining and programming data-processing pipelines for data analysis; writing software for data analysis, for conducting both prescribed analytical plans and exploratory data analyses; compiling of statistical and the creation of data visualizations. This position will report to the FHIL Research Lab Manager and take direction from the FHIL Director.

    Responsibilities

    Job Duties:

    Identify and integrate disparate data sources, both internal and external, including raw data from medical researchers, unstructured data from clinical experts, and well-established, publicly available databases.
    • Process and analyze laboratory data for research projects including assay development/validation across multiple platform pipelines.
    • Identify opportunities for process improvement; anticipate changes to data properties based on ongoing development of assay and analysis methods.
    • Provide subject matter expertise to research collaborators in the form of training, consultation, and other assistance as required.
    • Collaborate with internal and external partners on projects in support of the goals described above.
    • Document data management and analysis procedures.
    • Manage data science projects from creation to completion.
    • Communicate results to technical and non-technical audiences.
    Qualities Necessary For Success:
    • A strong desire to explore, investigate, dig, and generally uncover patterns and puzzles in data while maintaining a strong sense of thoughtful and pragmatic solutions.
    • Ability to advise investigators and management in clear language about results and new directions; strong oral and written communication and critical thinking skills are a must for this position.
    • Ability not only to work autonomously, but also to work collaboratively within multidisciplinary teams including statisticians, computational biologists, data engineers, epidemiologists, clinicians, administrators, etc.
    • Experience with messy, "real life" data sets.
    • Experience with working in a cloud environment (e.g., Amazon's EC2).
    • Knowledge of best practices in data analysis and scientific computing (e.g., literate programming, reproducible research).
    Qualifications

    Data Scientist I:

    Minimum Qualifications for Data Scientist I:
    • Masters or Ph.D. in Systems Biology, Bioinformatics, Statistics, Biostatistics, Mathematics, Computer Science, or equivalent required, with minimum two years of related experience working in a multidisciplinary team environment with statisticians, computational biologists, programmers, epidemiologists, and/or laboratory investigators.
    • Knowledge of immunology laboratory methods (e.g., immunoassays, flow cytometry) and resulting data outputs required.
    • Proficiency in R or Python and version control (Git, GitHub, etc.) required.
    • Strong communication skills (both oral and written), and critical thinking skills are essential.
    Preferred Qualifications for Data Scientist I:
    • Experience with programming in support of laboratory data management and analysis, clinical trials, or statistical programming in a clinical research setting strongly preferred.
    • Preference will be given to candidates who have experience working with vaccine immunogenicity assay data.
    • Proven ability to collaborate with various levels of internal and external partners, being able to work independently, with heavy multi-tasking.
    • Excellent interpersonal skills and professional diplomacy.
    • Excellent verbal and written communication skills.
    Data Scientist II:

    Additional Responsibilities for Data Scientist II:
    • Develop and deploy machine learning algorithms, predictive models, and classification methods to advance cancer research and inform clinical decision making.
    • Deliver novel, data-driven insights to improve outcomes in the treatment of cancer.
    • Identify areas of growth for the data science initiative and actively engage in enhancing the breadth and reach of data science across the Fred Hutch campus.
    • Collaborate with researchers and clinicians to identify high-impact opportunities for data science applications.
    Minimum Qualifications for Data Scientist II:
    • Bachelor's degree or higher in computer science, data science, statistics, informatics, or equivalent; an advanced degree (M.S. or Ph.D.) is preferred.
    • Core competency in at least one of the following: genomics, natural language, image processing, medical records or claims.
    • Experience in software development in the context of machine learning, such as R/Python, Weka, or others.
    • Sound understanding of software development best practices (e.g., version control, unit testing, regression testing).
    • Fundamental understanding of machine learning, both supervised and unsupervised, and experience with machine learning tools and applications.
    • Strong background in both formal statistics and predictive analytics, and some experience with the analytic process.
    • Software development in the context of machine learning, ideally in R or Python.
    • Strong written and oral communication skills, including report-writing, and presentation/visualization of analysis results.
    Preferred Qualifications for Data Scientist II:
    • A fundamental understanding of machine learning, both supervised and unsupervised, and experience with machine learning tools and applications.
    • A strong background in both formal statistics and predictive analytics, and some experience with the analytic process.
    • Software development in the context of machine learning, ideally in R or Python.
    • Strong written and oral communication skills, including report-writing, writing publications, and presentation/visualization of analysis results at seminars and meetings.
    • Proven ability to collaborate with various levels of internal and external partners, being able to work independently, with heavy multi-tasking.
    • Excellent interpersonal skills and professional diplomacy.
    • Excellent verbal and written communication skills.
    A statement describing your commitment and contributions toward greater diversity, equity, inclusion, and antiracism in your career or that will be made through your work at Fred Hutch is requested of all finalists.

    This role will have the opportunity to work partially at our campus and remotely.

    The salary range for Data Scientist I is from $93,101 to $139,630, and pay offered will be based on experience and qualifications.

    The salary range for Data Scientist II is from $99,445 to $157,144, and pay offered will be based on experience and qualifications.

    Fred Hutchinson Cancer Center offers employees a comprehensive benefits package designed to enhance health, well-being, and financial security. Benefits include medical/vision, dental, flexible spending accounts, life, disability, retirement, family life support, employee assistance program, onsite health clinic, tuition reimbursement, paid vacation days per year), paid sick leave days per year), paid holidays (13 days per year), paid parental leave (up to 4 weeks), and partially paid sabbatical leave (up to 6 months).

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