Data Scientist
CurrentDevelopment of models to predict performance of additives. - Develop and maintain models to predict performance of additive packages (statistical or machine learning models using Python or JMP)- Develop and maintain tools to consume models, focusing on the customer/consumer needs- Develop and maintain tools to optimise formulation packages, focusing on the customer/consumer needs- Lead and manage data science projects - from data retrieval to model consumption in production- Enable the use of Design of Experiments to generate innovative solutions to formulation challenges using JMP software (e.g. full factorial, mixture, definitive screening). - Consulting approach for varied business needs (e.g. data analysis) - customer centricity at core- Communicate ideas effectively to varied non-technical audiences- Work collaboratively with global colleagues throughout Infineum, across a diverse array of teamsPortfolio highlights:- image recognition for rig automation in the lab (tensorflow),- predictive modelling of chemical performance (scikit-learn or JMP),- mixture design for formulations (JMP), - chatbot using retrieval-augmented generation to answer questions using company data (Azure resources).Python libraries: numpy, pandas, scikit-learn, tensorflow v2, keras, AzureML SDKv2, etc.