Data Scientist (Sovereign Territory Surveillance) in Swindon

SRT Marine Systems plc (SRT) is a market leader in the domain of international marine surveillance technology and systems. We are a respected, established, and ambitious multi-national company headquartered in the UK with a global customer base. The company has a worldwide impact in the marine sector by leading the next generation of maritime domain awareness technologies (MDA), products, and systems that significantly enhance security, safety, environmental protection, and sustainability. Our customers range from the largest national coast guards to individual vessel owners.

We are now entering a new and strategically significant phase of growth, characterised by the expansion of our systems to incorporate Land Border Surveillance Systems. Our new Sovereign Territory Surveillance (STS) Systems will play a crucial role in enhancing civil defence security through the deployment of advanced automated security infrastructures. Utilised by nations worldwide, these technologies facilitate the monitoring of sovereign land borders, thereby strengthening border integrity and national security.

SRT's vision is to make innovative use of publicly available data, augmenting it with proprietary data as a differentiator in the Maritime Domain Awareness market. SRT sees Data Science and Machine Learning as an essential component to achieving this goal.

The role of Data Scientist is based in our Bristol office and aligned with our Hybrid working policy. As a Data Scientist, you will be part of a data-orientated team responsible for research and delivery. The team believes in the importance of collaboration to achieve its goals and values open, honest, and timely feedback. You will be encouraged to bring your knowledge, experience, ideas, and perspective to help solve the challenges put to you.

Responsibilities:

• Solve maritime and security-based problems such as detection and classification for time series and image/video data streams.
• Develop and evaluate ML models for behaviour classification, anomaly detection, and track pattern recognition within geospatial data.
• Research, prototype, extend, and optimise suitable vision and time-series models for these problems.
• Collaborate with developers to integrate model outputs into user-facing features.
• Work with infrastructure and edge-based engineers within SRT to build scalable pipelines for ingesting, processing, annotating, and managing large volumes of maritime data (e.g. AIS and vessel video footage).
• Contribute to feature development in areas such as alert generation and visualisation.
• Methodically apply best practices to document model performance, testing procedures, and experiment outcomes, while tracking datasets and model versions.

Requirements:

Essential:

• Solve maritime and security-based problems such as detection and classification for time series and image/video data streams.
• Develop and evaluate ML models for behaviour classification, anomaly detection, and track pattern recognition within geospatial data.
• Research, prototype, extend, and optimise suitable vision and time-series models for these problems.
• Collaborate with developers to integrate model outputs into user-facing features.
• Work with infrastructure and edge-based engineers within SRT to build scalable pipelines for ingesting, processing, annotating, and managing large volumes of maritime data (e.g. AIS and vessel video footage).
• Contribute to feature development in areas such as alert generation and visualisation.
• Methodically apply best practices to document model performance, testing procedures, and experiment outcomes, while tracking datasets and model versions.

Desirable:

• Experience fine-tuning, extending, and evaluating modern video or radar-based detection and tracking models, including appropriate performance metrics.
• Experience creating, managing, and interrogating graph databases (e.g., Neo4j).
• Experience with maritime, aerial, or other remote-sensing imagery.
• Exposure to MLOps tools (MLflow, Weights & Biases, Ray etc.)
• Experience deploying systems with containerisation, both on premises and in the cloud (e.g. using Docker and AWS ECS/ECR), and their ongoing maintenance/support.
• Experience of CI/CD within a machine learning/data science environment.

Benefits:

• Highly Competitive Salary and benefits package
• 25 days annual leave rising to 28 days with service
• Real individual development opportunities

SRT Marine Systems plc is an equal opportunity employer. We are committed to creating an inclusive environment for all employees and welcome applications from all backgrounds.