AEGIS London

Data Scientist

• Contribute across the full model lifecycle, from data preparation and development through deployment and monitoring
• Deliver data science projects from data preparation and exploratory analysis through model development and validation
• Work with the team to deliver models to production
• Take increasing ownership of deployment and in-life monitoring of built models
• Apply data science techniques to automate manual processes
• Explore generative AI use cases and assess their value and roadmap fitness
• Assess the quality and usefulness of internal and external data sources with data scientists and actuaries
• Produce ad hoc analytics and business insights coordinated through the Data Science and Data Analytics Manager
• Write clean, tested, version-controlled Python and participate in code reviews
• Contribute to Azure machine learning pipelines and learn MLOps and CI/CD patterns
• Monitor deployed products and engage with the business to track and measure adoption
• Document models clearly and explain them appropriately for a regulated environment
• Work with underwriting teams to understand operations and identify where data science can add value
• Capture and document requirements for data science products
• Work with IT and Data Engineering on project data
• Communicate findings and limitations clearly to non-technical audiences

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Data Scientist