Senior Data Scientist

Time Type:
Full time Working Pattern:
Hybrid Purpose of the Role Working closely with the Data Science Manager, the holder will strengthen the data science capability of the business by delivering models and actionable insights that improve underwriting profitability and unlock automation and efficiency across teams. This is a true end to end role: the holder will own projects from problem framing through development and deployment, and will remain accountable for their models in life, monitoring performance and drift and judging when a model needs retraining or retirement.

We are looking for someone who designs with a road to production mindset from the outset, with demonstrable experience of personally taking models into operational use. Technical delivery is only half the job. This role works directly and continuously with our commercial underwriters, from framing the problem through to adoption. The holder will translate underwriting requirements into data science solutions, build confidence in the results, and spend real time with underwriting teams understanding how each class operates.

Technically, we are looking for strong object oriented programming alongside ML, statistical and data analysis capability, and fluency in designing machine learning pipelines and deploying them (Azure in our case). MLOps and CI/CD experience is platform agnostic; the emphasis is on knowing the detail behind MLOps patterns actively contribute to raise MLOps standards across the team. Beyond delivery, the holder will act as an ambassador for the team, engaging across the business to capture and prioritise requirements and feeding these into a backlog that shapes the Data Science roadmap and sustains a consistent stream of value.

The right candidate will bring a mature mindset and genuine breadth across modelling, production grade programming, project management, commercial judgement along with the leadership and coaching skills to develop more junior colleagues. Close collaboration with Actuarial is expected from the outset, so experience of insurance pricing in a regulated environment, and comfort working alongside actuarial methodology, is a distinct advantage.

Effective stakeholder management is core; the right candidate will spend time with teams to understand the business and how each class operates.

Delivery of data science products Lead data science projects end to end, from problem framing and data preparation through development, deployment and ongoing monitoring in production. Work alongside the actuarial team to surface insights that drive performance (eg. Reserving). Apply data science techniques to automate manual processes across the business. Use generative AI to enrich insight and unlock new opportunities for the roadmap, deploying and maintaining these solutions through the same MLOps patterns applied to traditional models.

Research, assess and integrate external data sources, working with data scientists and actuaries to establish their quality, value and fitness for use. Address the data quality issues that constrain modelling, including the matching of premium and claims for delegated business. Support the business with proactive analytics and insights, coordinating delivery with the Data Science and Data Analytics Manager. Design, build and maintain machine learning pipelines in a cloud environment, applying sound software engineering practice.

Set and raise the team's standards for version control, testing, CI/CD, model versioning and reproducibility. Own deployed models in life, monitoring performance and drift and acting on degradation before it reaches the business. Ensure models are documented and explainable to a standard appropriate for a regulated environment. Work with technical and non technical stakeholders across the business to identify, document, analyse and prioritise requirements for data science products.

Coordinate with IT and Data Engineering to shape the data foundations these products depend on, and contribute to best practice and operational procedures for data management. Produce clear deliverables and communicate findings and their…