Autonomous Ocean Data Scientist

Biological Carbon Cycles; Southampton; Hybrid; GBP 35,000 - 39,000; Full time

Job summary

A leading oceanographic institution in Southampton seeks a candidate to analyze environmental data and develop Python tools for marine research. The role involves collaboration with engineers and researchers to convert observations into high-quality datasets. A MSc in a quantitative field is required along with strong Python programming skills and experience in time series analysis. The position offers opportunities for professional development in a multidisciplinary environment with generous benefits including annual leave and pension contributions.

Benefits

30 days annual leave

10% employer pension contribution

Employee Assistance Programme

Cycle2Work scheme

Flexible benefits portal

Qualifications

• MSc in physics, mathematics, engineering, earth sciences, or computer science.
• Experience in time series analysis and signal processing.
• Strong Python skills, including object-oriented approaches.
• Experience with version control systems such as Git.

Responsibilities

• Convert raw observations into high-quality datasets.
• Develop a standardised data processing pipeline for autonomous platforms.
• Design and implement Python tools and improve data workflows.

Skills

Python programming

Time series analysis

Signal processing

Collaborative development

Object-oriented programming

Education

MSc in a quantitative discipline

Tools

Git

Github

Gitlab

Job description

A leading oceanographic institution in Southampton seeks a candidate to analyze environmental data and develop Python tools for marine research. The role involves collaboration with engineers and researchers to convert observations into high-quality datasets. A MSc in a quantitative field is required along with strong Python programming skills and experience in time series analysis. The position offers opportunities for professional development in a multidisciplinary environment with generous benefits including annual leave and pension contributions.