Skills
- Programming (Python, Linux, Unix Shell Scripting)
- Data analysis and visualisation (Pandas, Xarray, Matplotlib, Numpy, Scipy, Seaborn, Jupyter)
- Machine Learning tools (scikit-learn, XGBoost)
- Engineering best practices (Git, GitHub, Unit Testing (pytest), Linting (black, mypy), Pair Programming, Code Review, Code Profiling, Code Reproducibility)
- Code optimisation and parallelisation (GitHub Actions, Argo)
- Statistical methods (Time series modelling, Regression, Bayesian inference)
- Database manipulation (SQL)
- Cloud computing (AWS)
- Analysis of large geospatial datasets (CMIP6, ERA5, WRF)
- Numerical models (Advanced Research Weather Research and Forecasting (ARW-WRF), Met Office Unified Model)
- Agile
Employment History
Freelance Data Scientist, Earthena AI (2023 – 2024)
Developed production-ready code, methodologies and documentation to ingest, preprocess and transform geospatial climate datasets. Used scientific expertise to design methodologies that integrate into existing preprocessing libraries. Included unit tests for key functions to ensure code reproducibility.
Climate Data Scientist, Cervest (2021 – 2023)
Developed production-ready code in extra-load-transform (ELT) pipelines and communicated high-level ideas and key results within the company. More specifically, developed and implemented innovative products offering climate risk information at asset level, pioneered our validation methodology for climate hazard products and developed an extreme wind product in a technical lead role.
Postdoctoral Research Assistant, Institute for Climate and Atmospheric Science, University of Leeds (2017 – 2021)
Analysed large datasets to investigate tropical cyclones and high-impact rainfall events over Southeast Asia, and published peer-reviewed papers on these phenomena. Alongside these responsibilities, prepared and delivered workshops on tropical meteorology for forecasters and scientists in Southeast Asia and at the Met Office.
Education
2012-2016: PhD: Atmospheric Science, University of Manchester, Manchester, U.K.
Thesis title: The 23–26 September 2012 UK Floods: Influence of diabatic processes and upper-level forcing on cyclone development
2007-2011: Master of Meteorology (MMet): Atmospheric Science, University of Reading, Reading, U.K.
Dissertation title: The influence of topography and diabatic forcing on numerically simulated squall lines
Courses and relevant information
Udemy The Data Science Course: Complete Data Science Bootcamp (2023)
- Statistics, Data Science, Python and Machine Learning exercises and challenges
EDX Python for Data Science (2021)
- Introduction to Data Science using Python
Consultant for Dorling Kindersley (2021-2023)
- Provided expert insight into the design and contents of three weather and climate children’s books in the Eyewitness series.