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 technical background in recommender systems, ranking systems, 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 ranking and recommender systems, 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 and ML 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 ML-driven solutions to product.
Strong proficiency in Python and its data-and AI-related libraries (e.g., Pandas, NumPy, Scikit-learn, PyTorch or Tensorflow).
Extensive experience with machine learning, NLP, and computer vision technologies.
Experience with ranking models in ecommerce marketplaces.
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.
