As a Data Scientist, you will:
Develop innovative predictive models fusing data and structured expert judgement to quantify risks related to geopolitics, conflict, crime, economics, cyber risk, ESG etc.
Draw from a diverse range of analytical methods appropriate for these problems, including Machine Learning, Natural Language Processing, statistical modelling, Probabilistic Graphical Models, Simulation.
Work closely with our data engineering team to ingest and structure the data you need.
Work closely with our visual analytics and development teams to communicate your findings and exploit the models you develop in intuitive customer facing applications.
Connect the outputs from such risk models to customer assets, exposures, projects and investments globally.
Monitor, analyse and communicate the performance of machines and human teams to quantify and help optimize performance of our systems.
Develop an understanding and knowledge of;
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
Practical risk and intelligence problems and processes from clients in insurance, tech, natural resources, finance and government.
Working as part of a multidisciplinary global team of industry, country and technical experts.
As a Data Scientist, you will be expected to have:
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
Deep curiosity about the world, and an academic or commercial track record developing creative analytical methods for making sense of it.
Professional experience developing and communicating models and statistical analysis in response to requirements.
Substantial experience in R or Python; proficiency in SQL queries.
Demonstrated mastery of verbal and written English
Experience In The Following Is Also Helpful:
Working with messy unstructured / semi-structured data, JSON.
Geospatial modelling / Geographic Information Systems (GIS)
NoSQL / graph databases