Key Purpose<\/p>\n
\tA highly skilled Senior Data Scientist who will provide the technical expertise to develop and integrate natural language processing (NLP), advanced large language models (LLMs), voice and image models to deliver business value leveraging generative AI. \u00a0These innovative capabilities will enable unstructured autonomous decision-making processes, increase operational efficiency, and deliver personalized customer experiences.
\n\tThis Data Scientist needs to remain abreast of the latest AI models and be experienced enough to work independently in researching and selecting the most optimal model and implementing this successfully within the business context.<\/p>\n
Areas of responsibility may include but are not limited to<\/p>\n
\tProject Delivery: By collaborating with contents specialists, data engineers and system architects, drive the deployment of solutions and delivery of projects from inception through to business adoption.
\n\tModel Development and Integration: Deploy robust and scalable LLMs that are integrated into AI frameworks, enhancing natural language processing capabilities.
\n\tAdvanced Data Retrieval Integration: Incorporate techniques like Retrieval-Augmented Generation (RAG), vector databases, and semantic searches to improve precision and relevance in data extraction from large datasets.
\n\tAutomation Workflows: Design and implement automation workflows that improve speed and accuracy of processes, reducing manual intervention and operational costs.
\n\tPerformance Metrics and System Maintenance: Develop performance metrics to consistently evaluate the efficiency and accuracy of AI models. Actively monitor and maintain these systems to ensure they remain effective and adaptable.
\n\tRegulatory Compliance: Ensure that all AI models and data handling practices comply with relevant laws and ethical guidelines, preparing documentation and reports as required for regulatory bodies.
\n\tExperimentation: Prototype ML systems and AI concepts, particularly those using NLP and LLMs, and evaluate the effects of different models and techniques on AI performance.
\n\tFuture Trends and Industry Insights: Continuously monitor advancements in AI and LLM technologies and review relevant academic literature and industry releases to ensure our strategies and implementations align with the latest innovations and standards.<\/p>\n
Knowledge and Skills<\/p>\n
\tSQL and working with databases.
\n\tPython for data science and machine learning.
\n\tCompetent with TensorFlow, PyTorch, NLP and LLM packages \u2013 Advantageous
\n\tFamiliarity with Azure services \u2013 Advantageous<\/p>\n
Education and Experience<\/p>\n
Education:<\/p>\n
\tMatric (Essential)
\n\tBachelor’s degree in Computer Science, Mathematics, Statistics, Data Science, Actuarial Science, Statistics, Operations Research, Industrial engineering, Applied Mathematics, or similar quantitative field.
\n\tHonours or Master’s Degree in relevant field.\u00a0<\/p>\n
\u00a0Minimum Experience: \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0\u00a0<\/p>\n
\tAt least 5 years proven experience in a data science environment.
\n\tProven track record in implementing ML workflows at scale, particularly using LLMs.
\n\tProven track record in handling, analyzing, and extracting insights from large and complex datasets, particularly unstructured text data.
\n\tPrevious experience tuning open source and proprietary large language models \u2013 Advantageous
\n\tPrevious experience with Voice and Image models \u2013 Advantageous
\n\t\u00a0<\/p>\n
go to method of application \u00bb<\/p>\n
Apply via company website ( ) or<\/p>\n
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