R Developer / Data Scientist / Statistician
R developer / Data Scientist / Statistician
Possess 15+ years R programming experience, 8+ years relevant work experience and 5+ years tutoring experience: have covered
wide range of supervised and unsupervised data science algorithms through D.Phil and M.Sc. in Statistics.
Lead programmer responsible for managing a team of 6.
Use R, Quarto, RShiny, HTML, CSS & JavaScript to support data processing, visualisation and statistical applications.
Developing and deploying a RShiny web application for reports.
Developing and deploying a RShiny web application for market partition processes.
Delivery within GSK Azure environment.
Code optimisation tasks to reduce latency and improve UX through HMTL, CSS, JavaScript parallelisation and asynchronous setup.
Led market and economic risk model development in R and RShiny.
Strong focus on automated testing and regulatory processes.
Covered A/B testing, NLP methods, regression and visualisation.
Reported deliverables through RShiny dashboards and RMarkdown using R, HTML, CSS, JavaScript and Git and Linux.
Assisted with development of credit and market risk models: included IFRS9 and CCAR scenario modelling and stress testing.
Collaborated with global team in an agile scrum.
Prototyped and developed marketing prognostic models.
Key techniques: GLMs, regression models, classification methods, random forests, non-linear methods and optimisation.
Applied data science algorithms including random forests and GLM regression models to business problems.
Worked alongside actuarial teams on data science projects using Git and Linux.
Built data visualisation tools including Shiny dashboards and pdf reports using R, RShiny, HTML, CSS and JavaScript.
Projects included creating an interactive RShiny US map to identify profitable regions for flood insurance using a random forest model.
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