Wayfair - Machine Learning Scientist - Python
1 month ago
Role :
We are looking for machine-learning scientists for the research and development of ML Scientists that power our real-time Search type-ahead, content recommendations, and algorithmic customer understanding experience. In this role, you'll partner with fellow scientists, engineers, analysts, and product managers to apply science and machine learning skills to directly impact Wayfair's revenue.
Responsibilities :
- Design, build, deploy, and refine large-scale machine learning models and algorithmic decision-making systems that solve real-world problems for customers.
- Work cross-functionally with commercial stakeholders to understand business problems or opportunities and develop appropriately scoped analytical solutions.
- Collaborate closely with various engineering, infrastructure, and ML platform teams to ensure the adoption of best practices in how we build and deploy scalable ML services.
- Identify new opportunities and insights from the data (where can the models be improved (What is the projected ROI of a proposed modification ).
- Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on.
- Minimum 1-2 years of experience with a PhD or 3+ years of industry experience with a Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
- Proficiency in Python or one other high-level programming language.
- Solid hands-on expertise deploying machine learning solutions into production.
- Strong theoretical understanding of statistical models such as regression, clustering, and ML algorithms such as decision trees, neural networks, etc.
- Strong written and verbal communication skills.
- Intellectual curiosity and enthusiasm for continuous learning.
- Experience with Python ML ecosystem (numpy, pandas, sklearn, XGBoost, etc. ) and/or Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML).
- Familiarity with GCP (or AWS, Azure), ML model development frameworks, and ML orchestration tools (Airflow, Kubeflow, or MLFlow).
- Experience in information retrieval, query/intent understanding, search ranking, recommender systems, etc.
- Experience with deep learning frameworks like PyTorch, TensorFlow, etc.
(ref:hirist.tech)
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