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Data Scientist – Sovereign Territory Surveillance
SRT Marine Systems plc. Solve maritime and security-based problems such as detection and classification for time series and image/video data streams .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and evaluating machine learning models for maritime and security applications, with a strong focus on video and radar-based detection, anomaly detection, and geospatial data analysis. Proficient in deploying scalable systems using containerization and MLOps tools to manage large datasets effectively.
Highest-signal resume keywords
Machine Learning Model DevelopmentVideo Detection and TrackingGraph Database ManagementMLOps Tools ExposureContainerization and Cloud Deployment
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningAnomaly DetectionBehaviour ClassificationGeospatial Data AnalysisModel EvaluationPerformance MetricsGraph DatabasesCI/CD in Machine LearningContainerizationCloud Deployment
Soft Skills
CollaborationDocumentation
Tools & Technologies
MLflowWeights & BiasesRayDockerAWS ECSAWS ECR
Industry Keywords
Maritime DataRemote-Sensing ImageryTime-Series ModelsAlert GenerationData Processing Pipelines
Tech Stack
Tools & technologiesAWSCloudDockerNeo4jRay
About the role
Key responsibilities & impact- 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
- Collaborate with developers to integrate model outputs into user-facing features
- Work with infrastructure and edge-based engineers to build scalable pipelines for ingesting, processing, annotating, and managing large volumes of maritime data, including AIS and vessel video footage
- Contribute to feature development in areas such as alert generation and visualisation
- Document model performance, testing procedures, and experiment outcomes while tracking datasets and model versions
Requirements
What you’ll need- 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
Comp & perks- Highly Competitive Salary and benefits package
- 25 days annual leave rising to 28 days with service
- Real individual development opportunities