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Geospatial Data Scientist (Boston) 2019 views


    • Participate in the R&D work of building enterprise geospatial feature engineering pipeline (e.g. binning data with spatial attributes).
    • Participate in the R&D work to improve DataRobot machine learning algorithms with geospatial modeling.
    • Lead the R&D project and implement data quality assessment algorithms (e.g. inlier and outlier detection) to improve the model accuracy.
    • Lead the R&D project and develop innovative solutions with a distributed computation framework to improve machine learning model performance.
    • Lead the R&D project and develop innovative solutions to improve model performance with heuristic model selection and retraining logic.
    • Lead the R&D project of developing machine learning models with monotonicity constraints and create new product features.
    • Lead the R&D project to improve the insights of insurance prediction models with exposure and offset.
    • Develop key modules to add multi-classification new features in the DataRobot machine learning platform.
    • Design and develop enterprise software to support machine learning applications in DataR
    • Design and develop enterprise testing modules/frameworks to support machine learning algorithm quality assessment.
    • Design and develop an innovative framework to improve machine learning algorithm performance (timing and memory) analysis.
    • Mentor new employees with onboarding plans and tutorials.
    • Make a technical presentation to deliver machine learning/software development knowledge to other
    • Participate in squad management and assist squad lead in reviewing software code and answering technical questions from

Main Requirements

    • Master’s degree in Computer Science, Information Systems Technology, Geoinformation Sciences, or related;
    • 2 years of experience as a Data Scientist, Developer, or related occupation;
    • 2 years of experience working with geospatial data and building geospatial prediction models to solve real-world problems;
    • 2 years of experience in building statistical and machine learning forecasting models and feature engineering pipelines;
    • 2 years of experience of building enterprise software with python; and
    • 2 years of experience of writing testable, documented and maintainable code.

Experience may be gained concurrently.

The employee has the option to telecommute full-time from any US location.


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