- Posted 08 November 2023
- Salary £45000 - £70000 per annum
- Discipline Actuarial & Risk
- Contact NameJono Conolly
We have partnered with a leading Lloyd's syndicate to find them a Data Scientist. The successful candidate will be responsible for defining the strategic data requirements for delivery of data consumption use cases. You will be interacting with all teams within the business to understand, capture, prioritise and document business and technical requirements leading to the deployment of automated, optimised and highly effective analytics solutions. This role further includes, but is not limited to:
- Data cleansing (e.g. matching of premium and claims for delegated business, cause codes).
- Work alongside actuarial team to perform data mining to produce extra insights to be available to underwriters to improve profitability (e.g. partnering with the underwriters to identify profitable micro-market segments).
- Using data science/AI techniques to automate manual tasks across the business (e.g. sanctions checks, fraud monitoring). d) Work with data analysts and actuaries to research, identify, cleanse, analyse, visualise and draw insights from external data sources.
- Work with the data analysts supporting the business with proactive analytics and insights.
- Work alongside actuarial team who will be able to use their business knowledge to extract key insights from the some of the more 'black box' data science techniques.
- Keep abreast of new and emerging data science techniques and advances in technology.
- Helps the Data Science Manager to define strategic data requirements for delivery of data consumption use cases:
- Collaborate with technical and non-technical stakeholders to identify, document, analyse, and prioritise data requirements.
- Facilitate communication and coordination with the IT team and Data Engineer to design effective data solutions that meet business needs.
- Create high-quality deliverables such as reporting specifications and visualisations.
Please apply for further information: