As a Data Scientist, you will:

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  Develop innovative predictive models fusing data and structured expert judgement to quantify risks related to geopolitics, conflict, crime, economics, cyber risk, ESG etc.

  
  


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  Draw from a diverse range of analytical methods appropriate for these problems, including Machine Learning, Natural Language Processing, statistical modelling, Probabilistic Graphical Models, Simulation.

  
  


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  Work closely with our data engineering team to ingest and structure the data you need.

  
  


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  Work closely with our visual analytics and development teams to communicate your findings and exploit the models you develop in intuitive customer facing applications.

  
  


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  Connect the outputs from such risk models to customer assets, exposures, projects and investments globally.

  
  


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  Monitor, analyse and communicate the performance of machines and human teams to quantify and help optimize performance of our systems.

  
  


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  Develop an understanding and knowledge of;

  
  
  
  
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    The structure and value of our unique proprietary datasets on global political, security and economics, part of 1500+ datasets from across financials, energy, automotive, and maritime

    
    
  
  
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    Practical risk and intelligence problems and processes from clients in insurance, tech, natural resources, finance and government.

    
    
  
  
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    Working as part of a multidisciplinary global team of industry, country and technical experts.

    
    
  
  
  
  

As a Data Scientist, you will be expected to have:

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  Bachelor’s degree and relevant working experience, or a Master’s or higher degree, in a relevant field of study (Statistics, Mathematics, Economics, Computer Science, Data Science, Social Science, Physics, Operations Research, Risk Management, Computational Biology etc.) with a strong quantitative component

  
  


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  Deep curiosity about the world, and an academic or commercial track record developing creative analytical methods for making sense of it.

  
  


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  Professional experience developing and communicating models and statistical analysis in response to requirements.

  
  


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  Substantial experience in R or Python; proficiency in SQL queries.

  
  


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  Demonstrated mastery of verbal and written English

  
  

Experience In The Following Is Also Helpful:

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  Working with messy unstructured / semi-structured data, JSON.

  
  


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  Geospatial modelling / Geographic Information Systems (GIS)

  
  


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  NoSQL / graph databases