In A Nutshell
Help transform real-time sensor data into 3D ocean carbon removal measurements.
Responsibilities
- Analyze and process large-scale, complex ocean sensor datasets.
- Conduct time series and spectral analysis of real-time, continuous data.
- Develop and refine algorithms and models used in ocean carbon flux analysis.
- Use Python and relevant data science libraries for data analysis and visualization.
- Develop API-based carbon flux algorithms, data transformations, and visualizations to inform Subtidal, its pilot partners, and customers about real-time carbon dioxide removals.
Skillset
- Master’s degree plus 3+ years of professional experience OR a PhD in data science, physical oceanography, or a related field, with a strong focus on data science, signal processing, or oceanographic data analysis.
- Experience developing algorithms and models for data transformations, ideally with a focus on carbon flux or similar ocean data analysis.
- Experience with oceanographic datasets (especially sensor data) and strong proficiency in handling large datasets is a plus, but candidates with strong data science skills in other sensor or environmental datasets will also be considered.
- Proficiency in Python, especially for data science and signal processing (Pandas, NumPy, SciPy).
- Experience with API development, ideally using Python frameworks like Flask or Django.
- Expertise in time series analysis and spectral analysis of real-time data.
- Ability to work with large, complex datasets, particularly oceanographic sensor data.