Erik Becker
Senior Meteorologist | Weather Analyst
17 years of professional experience bridging meteorology and data science into cutting-edge, data-driven solutions for decision-making.
I am a meteorologist and data scientist who designs and builds modern web-based dashboards and analytical tools that translate complex atmospheric and climate data into clear, actionable insight. By combining deep domain expertise in weather and climate science with robust software engineering and data-visualization practices, I develop intuitive platforms that enable rapid interpretation, scenario awareness, and confident decision-making. These tools are engineered not just to display data, but to support real-world operational and strategic decisions where timing, clarity, and accuracy matter.
Core Competencies:
Weather & Forecasting
● Operational forecasting - Australia, Southeast Asia, South Africa
● Global weather pattern and teleconnections analysis (ENSO, MJO, IOD, etc.)
● Numerical Weather Prediction (ECMWF, GFS, ACCESS, ICON, JMA, etc.)
● Multi-model and multi-ensemble interpretation
● Impact based forecasting
● Deterministic, probabilistic, and spatial forecast verification
● Analogue-based seasonal and subseasonal outlooks
● Tropical cyclone monitoring and risk assessment
● Floods, severe convection and thunderstorm monitoring & forecasting
Radar, Satellite & Nowcasting
● Weather radar and satellite theory
● Data Quality Control (QC) & compositing
● Quantitative Precipitation Estimation & Forecasting
● Radar–rain-gauge integration and geostatistical methods
● Object-based storm identification and tracking (LROSE)
● Optical-flow-based extrapolation and semi-Lagrangian methods (pySTEPS, S-PROG, SwirlsPy)
● Experience with geostationary satellite data (e.g. Himawari)
Data Science & Machine Learning
● Regression Modelling
● Clustering Algorithms
● Keras, Tensorflow & PyTorch
● Deep learning architectures: DNN, CNN, U-Net, ConvLSTM, GAN
● Custom loss functions and domain-specific objective design
● Time-series modelling and forecasting
● Ensemble and probabilistic modelling workflows
Programming & Software Development
● Python (expert), R, C++, Fortran, Java
● Git version control
● Linux and Bash scripting
● Object Oriented Programming
● Asynchronous programming
● Parallel computing on CPU and GPU architectures
● HPC environments and schedulers (PBS)
● Performance optimization for large-scale numerical workloads
Geospatial & Remote Sensing
● GIS and geospatial processing: GDAL, QGIS
● Radar and environmental data tools: wradlib, Py-ART
● Spatial data handling, analysis, and visualization
● Interpolation methods (IDW, Kriging)
Web, Dashboards & Operational Tools
● Web frameworks and dashboards: Streamlit, RShiny, Flask
● Front-end technologies: HTML, CSS
● Development of operational monitoring and decision-support tools
● Containerization: Docker, Singularity
● Real-time data pipelines and automated monitoring systems
● Cloud and distributed data platforms (Databricks, Dremio)
Energy & Commodity Markets
● Power demand modelling, wind & solar generation forecasting
● Research links between weather patterns and power, LNG and agricultural market drivers
● Development of weather-driven trading indicators
Communication & Leadership
● Presentations to traders, quantitative teams, and management
● Daily operational forecast briefings
● Clearly describe potential uncertainties and risks
● Technical communication with governmental partners
● Leadership of multi-disciplinary technical teams
● International scientific collaboration
● Scientific writing and documentation
● Lecturing, mentoring, and knowledge transfer