• Applying and deploying large language models/generative AI models such as GPT-4, Gemini, and other open-source models (Mistral, LLaMA, Phi) to support digital merchandising. • Creating and maintaining detailed dashboard reports in Looker Studio to provide real-time insights for management. These dashboards include key performance indicators (KPIs), trend analysis, and detailed visualisations to support data-driven decisions.• Using Google BigQuery and its Python client to perform efficient data querying and storage. This involves writing complex SQL queries, optimising data retrieval, setting up scheduled queries and views, and regularly extracting, transforming, and loading (ETL) data to keep datasets up-to-date for analysis.• Developing and sustaining programmes that automate and speed up the product line extension (PLE) process. This includes creating scripts and tools to streamline adding new products, ensuring accurate product information, and integrating new products seamlessly into existing categories and merchandising strategies.• Designing and implementing an anomaly detection model that uses NLP and text embeddings to identify miscategorised products and propose appropriate categories, thus improving product discoverability and user experience. This led to the reduction of miscategorised products on site by 20%.• Employing advanced unsupervised machine learning techniques (clustering), NLP and word embedding models to create product variants and families. This process enhances user experience by grouping similar products, improving site navigation, and increasing sales through better product recommendations.• Developing and overseeing several vector databases to facilitate fast data retrieval and analysis. These databases are used for product categorisation, querying similar products, and more, supporting quick access to relevant data and enhancing decision-making and operational efficiency.

• Performed data analysis and built tailored data visualisations with Python and R to illustrate complex datasets in an understandable and engaging manner, facilitating client decision-making.• Applied NLP techniques using libraries like spaCy and NLTK to analyse and derive insights from text data.• Collaborated with diverse clientele across sectors such as cybersecurity, healthcare, academia, and many others to address unique business challenges through data-driven solutions.• Designed, implemented, and evaluated machine learning models, including but not limited to Random Forest, Linear Regression, XG Boost and K-means clustering to extract insights and drive business decisions for diverse clientele.