Senior Data Scientist (12 Month Contract)

Senior Data Scientist (12 Month Contract) Job Description

We're looking for a Senior Data Scientist to join our Digital team and help deliver predictive analytics solutions that support pricing, underwriting, claims, and broader digital transformation initiatives.

In this role, you will:

• Lead advanced analytics initiatives that support insurance portfolio management and commercial performance.
• Apply statistical and machine learning techniques to generate insights that improve decision-making.
• Work across structured, unstructured, and externally sourced data to identify opportunities and enrich analytical outcomes.
• Extract, prepare, and analyse data using Python and other data management tools.
• Develop predictive models and analytical solutions using techniques such as GLMs, gradient boosting, tree-based models, and other machine learning methods.
• Partner with business teams to understand needs, scope analytical work, prioritise initiatives, and shape the analytics roadmap.
• Collaborate with the Global Analytics team on model build and refinement, providing technical feedback and ensuring solutions meet business and quality standards.
• Drive end-to-end delivery from problem framing and exploration through to model development, validation, deployment, and adoption.
• Present analytical findings, model performance, and portfolio insights to business stakeholders, actuarial teams, and other key partners in clear, decision-ready language.
• Maintain comprehensive documentation across the solution lifecycle, including business requirements, solution design, model logic, and validation outcomes.

Qualifications

• Bachelor's or Master's degree in data science, statistics, mathematics, actuarial science, computer science, engineering, or a related quantitative discipline.
• 5+ years of hands on data science and advanced analytics experience.
• Strong understanding of machine learning and statistical concepts, including supervised and unsupervised learning, GLMs, gradient boosting, anomaly detection, simulation, NLP, text analytics, and deep learning.
• Strong technical proficiency in Python and common data science / machine learning libraries such as pandas, scikit learn, statsmodels, XGBoost, LightGBM, PyTorch, or TensorFlow.
• Practical experience with modern data platforms such as Databricks and Snowflake.
• Experience working with structured and unstructured data, including sourcing, evaluating, and integrating external data.
• Experience building and maintaining data and ML pipelines, with familiarity in MLOps practices such as deployment, monitoring, drift detection, and retraining.
• Experience working in agile delivery environments, using tools such as Jira and Confluence to plan, prioritise, and track work.
• Excellent communication and presentation skills, with the ability to engage actuarial, technical, and senior business stakeholders confidently.
• Curious, analytical, and detail oriented mindset, with strong ownership, problem solving ability, and end to end delivery capability.
• Experience in AI or model driven analytics is highly regarded.
• An actuarial background will be considered an advantage.