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    Senior Machine Learning Scientist - Chevy Chase, United States - The Knot Worldwide

    The Knot Worldwide
    The Knot Worldwide Chevy Chase, United States

    3 weeks ago

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    Description
    :

    At The Knot Worldwide, the Data Team is driving innovation through data-driven solutions across our online wedding marketplaces. We are looking for a Senior Machine Learning Scientist with a strong background in Predictive and Descriptive Modeling, Natural Language Processing, Computer Vision, and embedding-based approaches to join our dynamic Machine Learning team. This role requires experience in building and deploying AI & ML models from concept to production.

    Key Responsibilities:
    • Develop comprehensive data-driven solutions by applying advanced machine learning techniques, including both supervised and unsupervised learning.
    • Design and implement models for Natural Language Processing and Computer Vision to enhance our product offerings and operational efficiency.
    • Collaborate closely with product stakeholders and engineering teams to define clear objectives, deliverables, and timelines for data science projects.
    • Lead the end-to-end lifecycle of data science projects from data exploration and model building to deployment and performance monitoring in production environments.
    • Employ robust MLOps practices to ensure the scalability and maintainability of models in production.
    • Continuously evaluate emerging technologies and methodologies to drive innovation and improve the existing capabilities of the data science team.
    Successful Candidates have:
    • Master's or PhD in Computer Science, Data Science, Statistics, or a related field.
    • Minimum of 5 years of experience in a Data Science and Machine Learning role with a proven track record of deploying large-scale data-driven solutions.
    • Strong proficiency in Python and its data-related libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch).
    • Extensive experience with machine learning, NLP, and computer vision technologies.
    • Demonstrated experience with MLOps tools and frameworks to manage the lifecycle of machine learning models in production.
    • Excellent communication skills with the ability to articulate complex quantitative analysis in a clear, precise, and actionable manner.
    • Experience advising data scientists and collaborate across cross-functional teams.
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