We learned to apply statistical data analysis and machine learning to diverse datasets ranging from unstructured text to large volumes of transactional data. To complement my data science skills, I was also provided with a foundation in relevant data technologies to build solutions. These included Python, SQL, Docker, Spark, and the AWS ecosystem

• Claim analytics - Created a model to predict the claim severity from unstructured emails notifying of a loss. I developed a named entity recognition pipeline in Spacy to highlight key information to be used in the claims assessment process.• Email triage – Created a model to triage incoming emails from brokers. I developed the end-to-end integration, with the training data generation and mailbox integration being developed using UiPath. The machine learning model was then deployed using TeamCity and Octopus and versioning and hyperparameter tuning was tracked using MLflow. The model was finally made available to the RPA process using FastAPI.

· Focused on the development of a distillery to deal with waste molasses produced during the sugar manufacturing process.· Assessed the feasibility of various distillery plans considering environmental and economic factors. Presented these findings in a techno-economic report to help advise internal investors.· Created a bespoke financial model of a future distillation plant at the site, complete with sensitivity analysis, potential increased revenue and cost calculations. This model considered biomass generation from their own sugarcane factory, existing boiler and turbine capacity and potentially buying additional molasses to increase revenue.

Consultancy project for an AI analytics company.· Conducted research on the ethical implications of the development of artificial intelligence. Specifically, its potential economic impact in industry and developing countries.· Collaborated on an industrial report and presented findings to a group of consultants.