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Posted 2h agoMadrid | Madrid

Senior Data Scientist, Graph Risk Analytics

SeniorHybrid (Madrid)€95,000 – €115,000 / mo
Required Skills
PythonSQLMachine Learning
Job Description
Location: Madrid, Spain
Annual Remuneration: €95,000 - €115,000 and discretionary annual bonus
Pay Frequency: Monthly
Probationary Period: 180 days
Work Arrangement: Hybrid, 3-days per week

TL;DR Kharon is seeking a full-time Senior Data Scientist, Graph Risk Analytics based in Madrid. 


Key Responsibilities

Responsibilities:
  • Taking ownership of Kharon's risk propagation and entity analytics system — the engine that evaluates entities in our knowledge graph and surfaces meaningful risk signals to customers
  • Designing and implementing complex analytical logic that translate nuanced geopolitical and financial risk into structured, interpretable outputs
  • Building and maintaining scalable data pipelines and graph-based ML systems that power risk scoring and entity analysis
  • Partnering closely with Research, Product, and Engineering teams to understand evolving risk frameworks and translate them into robust, maintainable systems
  • Iterating on the system's architecture to increase the complexity and precision it can handle — this is not a rip-and-replace, but a thoughtful evolution of a system already in production
  • Exploring how LLMs and other AI techniques can be integrated to handle increasingly complex risk logic


Skills & Knowledge

  • A proven interest or experience in global security, financial crimes, sanctions, export controls, or related domains
  • 4+ years of experience as a Data Scientist, with demonstrated ownership of production systems
  • Strong foundation in statistics and the ability to apply quantitative methods to complex, real-world problems
  • Proficiency in Python, SQL, and working with graph databases or knowledge graph structures
  • Experience with graph analysis, graph ML, or network analysis — professional experience is a strong differentiator
  • Comfort working across research and data engineering contexts — this role spans all three
  • Experience with Docker, Kubernetes, and API development
  • Strong product instincts — able to go deep technically while staying aligned to customer and business outcomes
  • Bonus: Experience with LLMs or AI-assisted analytical systems

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