September 11
🔄 Hybrid – London
• Design, implement, and fine-tune innovative search algorithms to improve search relevance, accuracy, and performance. • Develop and optimise NER models to better understand and classify entities within user queries. • Build and refine models for user queries, ensuring robust and user-friendly search experiences. • Conduct detailed data analysis to identify search performance issues, and design A/B tests.
• 3+ years of experience as a Data Scientist using Natural Language Processing (NLP) techniques. • Have used Named Entity Recognition (including tokenization, Part-of-Speech tagging, feature extraction and modelling). • Experience with fuzzy matching algorithms like Levenstein distance and n-grams for handling spelling errors and typos. • Proficient in building and fine-tuning complex machine learning models, including feature engineering, and hyperparameter tuning. • Deep understanding of model evaluation and validation techniques. • Python expert, proficient in writing efficient, production-ready code. • Knowledge of software engineering best practices such as testing, CI, and version control. • Able to summarise findings to non-technical stakeholders effectively.
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