OSINT Analyst - Vessel Identification

Role Overview

Automated tools can detect vessels but often fall short in precise identification, especially when encounters involve vessels without AIS data, spoofed identifiers, inconsistent naming and IMO numbers, or low-confidence model outputs. In these complex scenarios, the OSINT Analyst serves as a critical adjudication layer, supplementing machine detections with verified identities supported by robust evidence and explicit confidence levels.

Key Responsibilities

• Resolve ambiguous or challenging vessel identifications by attaching verifiable details such as name, IMO, owner, operator, and flag, backed by dependable evidence.
• Conduct investigations into vessel identity manipulations including AIS data gaps, GNSS spoofing, MMSI duplication, name and flag alterations, and vessel substitutions.
• Employ open-source intelligence methods: analyze satellite and optical imagery; consult ship photo databases, vessel registries, ownership records, port and terminal documentation, classification societies, insurance data, and open reports.
• Reconstruct vessels’ historical ownership and behavioral patterns to provide contextual understanding beyond single detections.
• Produce structured, well-sourced identification records with clear provenance and carefully articulated confidence assessments.
• Contribute to improving automated detection models by delivering accurate ground truth data and highlighting edge cases for data science teams.
• Maintain high standards of sourcing integrity and data accuracy within the team to ensure trustworthiness of vessel records.

Required Qualifications and Experience

• A minimum of three years’ experience in intelligence, investigative research, maritime analysis, or allied OSINT disciplines, with the ability to synthesize fragmented evidence into defensible conclusions.
• Familiarity with the maritime sector, including vessel classifications, AIS systems, registries, ownership structures, and shipping operations.
• Strong open-source intelligence skills encompassing source discovery, cross-validation, dealing with uncertainty, and maintaining provenance.
• Competence interpreting various imagery types such as satellite, optical, and preferably SAR imagery to understand detection data.
• Meticulous documentation habits and clear written communication, emphasizing careful confidence and caveat language.

Preferred Attributes

• Knowledge of sanctions regimes, trade compliance, and tactics employed for evasion, such as shadow fleets, ship-to-ship transfers, and chokepoint activities.
• Experience working with labeled data sets or collaborating with data science teams on machine learning workflows.
• Familiarity with GIS, geospatial tools, and managing large data volumes.
• Additional language skills relevant to key shipping and registry countries.

Behavioral Competencies

• Demonstrates a rigorous, evidence-driven approach emphasizing corroboration and minimizing unsupported assertions.
• Able to operate confidently amid ambiguous information and make defensible judgments.
• Organized and systematic, efficiently managing a workload of investigative tasks under time constraints.
• Effective written communicator, tailoring reports for analysts, compliance teams, and leadership.
• Curious and collaborative, committed to continuous improvement and enhancing team tools.

Educational Background

Possession of a Bachelor's or Master's degree in international relations, security or intelligence studies, maritime studies, geography, data science, or related domains, or equivalent professional experience.

Company Ethos

Our company thrives on innovation, collaboration, and customer focus. We prioritize decisive action, teamwork, and a supportive environment fostering relationships and creative problem-solving.

Diversity and Inclusion Commitment

We encourage applications from all backgrounds and experiences and strive to maintain an equitable and inclusive workplace. We recognize the value of diverse perspectives and aim to reduce barriers to application, welcoming underrepresented groups to apply even if all qualifications are not perfectly met.

Privacy Acknowledgement

Applicants confirm their understanding and acceptance of the applicable Staff Privacy Notice.