ECMWF is looking to fill 2 positions as Associate Hydrological Data Analyst (A1) that are part of a dynamic and diverse group of experts developing and running the CEMS Hydrological Forecast Computational Centre. Joining the Centre as in this role you will work at the forefront of delivering the world-leading European and global hydrological forecast service, contributing to and running hydrological models to generate and made widely available reference and forecast datasets. You will also work with other data analysts to summarise the hydrological status and forecasts information and to explore how to integrate advanced methods and technologies (e.g. Machine Learning) into the processing chain for the delivery of computationally effective, high impact forecast products.
You will have an opportunity to work at the core of the EFAS and GloFAS Early Warning Systems (EWS) delivery of the Copernicus Emergency Management Service. You will develop tools and conduct critical analyses associated with the EWS cycle releases (generally every one to two years) to ensure that the resulting hydrological forecast products retain their world-leading edge and continue to respond to the needs of users.
You will be part of the group responsible for developing and running hydrological forecasting systems at ECMWF. Their Evaluation Section's Environmental Forecast team. This is an outstanding opportunity to gain hands-on experience with hydro-climate data and forecast production while working closely with scientists and experts in a science driven, world-leading and innovative international organisation. In your role you will actively contribute to delivering the next generation of Early Warnings Systems, helping to mitigate against some of the most devastating impacts of the climate crisis.
- Help develop tools for hydrological data analysis and visualisation
- Contribute to EWS cycle upgrade activities and benchmarking against previous cycles
- Run hydrological forecast experiments and analyse results
- Contribute to CEMS-Flood activities such as generation of maps and graphs for outreach activities, data preparation and station mapping for the modelling
- Contribute to the archiving and dissemination of CEMS-Flood data through the Climate Data Store (CDS)
- Investigate the use of Machine Learning, propose and implement actions to improve the quality and robustness of global hydrological forecasting
- Contribute to CEMS-Flood shared operational duties
- Write scientific documentation and extract visual outputs
- Contribute to reporting activities and projects meetings