Senior Data Scientist — End-to-End ML & MLOps

Aegis London; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

AEGIS London is seeking a data science professional to strengthen our capability by delivering end-to-end models and actionable insights that improve underwriting profitability and automate processes. You will own projects from framing through deployment, monitor model performance and drift, and guide production-ready design with a production mindset.

Collaborating with underwriters and actuarial teams, you will translate requirements into data science solutions, surface insights, and drive

Qualifications

• Production-grade Python with OO design, testing and review practices.
• Experience taking models into production and supporting them in life.
• ML toolkit: scikit-learn, pandas, NumPy; model validation & data support.
• Software engineering fundamentals: version control, testing, deployment, environments.
• MLOps/CI-CD in practice; platform-agnostic patterns and governance.
• Cloud ML delivery, ideally on Azure (Azure ML/DevOps); AWS/GCP also acceptable.
• SQL and relational data modelling against large datasets.
• Data wrangling for messy insurance data.

Responsibilities

• Lead data science projects end-to-end, from framing to deployment and monitoring.
• Surface insights with underwriting teams and drive performance improvements.
• Automate manual processes with data science techniques across the business.
• Use generative AI to enhance insights and roadmap opportunities with MLOps.
• Integrate external data sources and assess data quality and fitness for use.
• Address data quality issues affecting modelling, including premium/claims matching.
• Provide proactive analytics and coordinate delivery with Management.

Skills

Python

ML deployment

MLOps

CI/CD

Azure

SQL

Data wrangling

Communication

Tools

Azure ML

Python

SQL

Pandas

NumPy

Power BI

Job description

AEGIS London is seeking a data science professional to strengthen our capability by delivering end-to-end models and actionable insights that improve underwriting profitability and automate processes. You will own projects from framing through deployment, monitor model performance and drift, and guide production-ready design with a production mindset.

Collaborating with underwriters and actuarial teams, you will translate requirements into data science solutions, surface insights, and drive