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 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.
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