Who are we?👋
Look at the latest headlines and you will see something Ki insures. Think space shuttles, world tours, wind farms, and even footballers’ legs.
Ki’s mission is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days.
Ki is proudly the biggest global algorithmic insurance carrier. It is the fastest growing syndicate in the Lloyd's of London market, and the first ever to make $100m in profit in 3 years.
Ki’s teams have varied backgrounds and work together in an agile, cross-functional way to build the very best experience for its customers. Ki has big ambitions but needs more excellent minds to challenge the status-quo and help it reach new horizons.
Where you come in?
The Data Analyst at Ki works at the intersection of analytics, engineering and product. They work within teams and across Ki’s teams to support and drive design, development, and optimization of analytics, data models, reports, and other data-driven products that support strategic business goals.
What you will be doing: 🖋️
Applied Analytics
- Develop knowledge and expertise in Ki’s business domains to generate insights and measurement on initiatives that drive company objectives.
- Collaborate with business stakeholders to identify opportunities for leveraging data analytics to drive commercial results and improve operational efficiency.
- Identify opportunities to leverage data analytics techniques to extract value from both internal and external data assets to enrich analytical capabilities.
Analytics Engineering
- Develop and maintain the core data sets underlying the suite of analytical tools used by the team
- Create and maintain data visualizations and dashboards using tools such as Tableau, Power BI, or similar.
- Develop scalable data solutions that conform to Ki’s technology and engineering principles and industry best practice.
Data Management & Governance
- Preserve the integrity of data, making sure it is accurate, consistent, and reliable throughout its lifecycle.
- Investigate and lead timely resolution of emerging issues with underlying data systems and models as and when these arise.
- Ensure that domain data is managed and used according to Ki’s data governance policy and best practice principles.
Other
- Ensure all data systems and models are documented in line with Ki wide standards
- Recommend ways to improve data efficiency and reliability
- Increase the degree of automation within the team’s data systems and tools
- Investigate new tools that would help the team store, structure and analyse data.
Requirements
- Proficiency in SQL and Python to manipulate and analyse datasets
- Experience with data reporting and visualisation tools (e.g. Tableau, Looker, Dash, Streamlit)
- Solid understanding of statistical techniques (e.g. regression, clustering, correlation analysis), with ability to apply these to commercial problem solving.
- Experience working in cloud native environments (especially GCP) would be plus.
- Experience with designing and implementation of data structures to ensure ease of use and accessibility by a broader audience.
- Self-organised, good at documenting and communicating findings and approach.
- Excellent communicator, able to present complex analysis to both technical and non-technical audiences.
- Experience working in a regulated industry
What to expect during the recruitment process:
- Initial recruiter screening call
- Interview with hiring manager
- Technical Interview (this may vary depending on the role)
- Values Interview
