Data Scientist/Modeller

  • Full-time

Company Description

About Sibylline

Sibylline is a leading intelligence and strategic risk consultancy in the security sector. Since 2010 we have supported businesses, governments and NGOs by providing high-quality risk analysis, due diligence and consultancy services.

The firm provides an innovative, entrepreneurial and fast-growing working environment, offering employees ever greater exposure to high-profile clients and challenges. Sibylline offers fantastic opportunities for career progression within a successful company, and we aim to help our employees build their own personal profiles as well-regarded analysts within the broader industry.

Key attributes of Sibylline employees are:

  • Self-motivated, and auto-improving individuals who can couple initiative and boldness with good judgement
  • Excellent written and spoken English
  • Clarity of thought and analytical flair
  • Strong, demonstrable interest in security and intelligence
  • The ability to work under pressure, demonstrate leadership when required but also be able to collaborate effectively in teams
  • Excellent attention to detail

Job Description

Role Summary

We are building Sibylline’s core data and intelligence platform to support real-world security, geopolitical, and risk decision-making. We are seeking a Senior Data Scientist specialising in applied modelling to develop analytical models and AI-enabled methodologies that combine quantitative data, qualitative assessment, and expert judgement. 

This role focuses on building indices, indicators, trend analyses, and structured assessments across areas such as geopolitics, crime, security, public health, and societal risk. A key part of the role involves using Large Language Models (LLMs) to support qualitative analysis at scale, to, for example, extract signals from text, structure expert assessments, enrich data, and support transparent, auditable analytical workflows. 

Your work will be embedded directly into a developing enterprise SaaS intelligence platform to be used by analysts and clients globally. 

This is a hands-on role suited to someone who enjoys working at the intersection of data science, qualitative analysis, and applied AI, and who is comfortable operating in complex, ambiguous real-world domains. 

This is a remote role working 9 am - 5 pm, Monday to Friday, requiring occasional travel to London. The London office is available to work in if desired.  

Responsibilities  

  • Designing and maintaining quantitative models, indices, and scoring frameworks for diverse areas such as geopolitical, security, crime, and societal risk 
  • Developing methodologies that combine structured qualitative judgement with quantitative data 
  • Using LLMs to support qualitative analysis at scale (e.g. text analysis, signal extraction, summarisation, classification, enrichment) 
  • Designing AI-enabled analytical workflows that are transparent, explainable, and suitable for client-facing intelligence products for internal and external products 
  • Analysing trends across time and geography using heterogeneous data sources (structured, semi-structured, and unstructured) 
  • Validating, stress-testing, and iterating models as new data and intelligence become available 
  • Clearly documenting assumptions, methodologies, and limitations for both technical and non-technical stakeholders 
  • Working closely with intelligence analysts, product managers, and software engineers to embed models and AI workflows into production systems 
  • Contributing to the development of Sibylline’s analytical, modelling, and AI governance standards 

Knowledge, Skills, and Abilities  

  • Strong experience in applied data science, quantitative modelling, or analytical research in real-world decision-making contexts 
  • Desired: prior experience in geopolitical or geoeconomic modelling 
  • Proficiency in Python for data analysis and modelling 
  • Working knowledge of SQL and similar technologies for querying and manipulating data 
  • Desirable: knowledge of frontend development including React, Typescript 
  • Experience building indices, indicators, forecasts, or composite scoring systems 
  • Ability to structure and formalise qualitative judgement and expert assessment 
  • Hands-on experience using LLMs in applied analytical workflows (e.g. prompt design, evaluation, chaining, or hybrid human–AI analysis) 
  • Strong statistical reasoning and data analysis skills 
  • Proficiency in Python (or similar) for data analysis and modelling 
  • Experience working with time-series, geospatial, event-based, or text data is highly desirable 
  • Prior experience in geopolitical or geoeconomic modelling is highly desirable 
  • Strong interest in geopolitics, security, crime, public health, or societal risk 
  • Comfortable working in a trusted environment and eligible for background screening 

Qualifications  

  • Degree in a quantitative or analytical discipline (e.g. data science, statistics, economics, mathematics, political science with quantitative focus, epidemiology, or similar) 
  • Experience working with intelligence, risk, or security-related datasets 
  • Familiarity with model interpretability, explainability, and AI governance in applied settings 
  • Experience collaborating with software engineering teams to productionise analytical and AI-driven outputs 

Additional Information

Interview Process   

  • Initial call with our Talent Acquisition team member  
  • 30-minute video call with the hiring manager  
  • Home task  
  • Panel interview with some of the team members and hiring managers at Sibylline  

Research indicates that certain groups are less likely to apply for a position unless they meet every single requirement. If you feel you meet some of the requirements and can offer a unique perspective to this role, we strongly encourage you to apply—you might be the perfect fit we're looking for! 

Sibylline is committed to the recruitment and selection of candidates without regard for sexual orientation, gender, ethnicity, age, political beliefs, culture, and lifestyle. We are committed to fostering a business culture that reflects these values and promotes equal opportunity. 

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