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Model Development & Optimisation Train and optimise models for new data providers, ensuring seamless integration. Enhance models for dynamic input handling. Improve LDA model performance to handle a higher number of clusters efficiently. Optimise RAG (Retrieval-Augmented Generation) architecture to enhance recommendation accuracy for large datasets. Upgrade Retrieval QA architecture for improved chatbot performance on large datasets. Develop and optimise forecasting models for marketing, demand...
About the Role
Job Description:
We are looking for a Data Scientist with expertise in Python, Azure Cloud, NLP, Forecasting, and large-scale data processing. The role involves enhancing existing ML models, optimising embeddings, LDA models, RAG architectures, and forecasting models, and migrating data pipelines to Azure Databricks for scalability and efficiency.
Model Development
Forecasting & Time Series Modelling
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