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For Companies At a Glance
- Tasks: Join our Algorithmic Underwriting team as a Data Analyst, focusing on data-driven insights and analytics.
- Company: Ki is a leading global insurance tech company revolutionising the specialty insurance market since 2021.
- Benefits: Enjoy competitive pay, recognition for hard work, and a diverse, inclusive workplace culture.
- Why this job: Be part of a digital transformation in insurance, using your skills to make a real impact.
- Qualifications: Experience with BI tools, Python, and statistical techniques like regression and clustering is essential.
- Other info: We value diversity and encourage everyone to bring their unique perspectives to the team.
The predicted salary is between 36000 - 60000 £ per year.
Who are we?
Ki is the biggest global insurance tech company you’ve never heard of, unless you’ve been looking to insure a satellite, wind farm or music festival recently.
Having written over $877m in gross written premium in 2023, we’ve achieved significant growth since our beginnings in 2021. Our investors were excited about the fact we were revolutionising the way a 333 year-old industry was working. There are hardly any industries left that are mainly paper based, but the specialty insurance market is one. Together with partners at Google and UCL we developed Ki and created a platform that helps insurance brokers place risk in a fast and frictionless way. We’re continuing to lead the charge on the digitisation of this market and we need more excellent minds to work with us to realise this goal and create more opportunities.
What you will be working on
We\’re looking for a Data Analyst to join our Algorithmic Underwriting team, where you’ll be working with teams across Ki to focus on digitisation of the underwriting process through delivery of value-adding analytics and insight, build and enhancement of data-driven products, and fostering a culture of data-driven decision making.
Bringing your experience of building dashboards in a modern BI and Python you will support development of data visualisation initiatives including design, build and maintenance ensuring they meet business requirements and user needs. You’ll be generating valuable data insights for the business, whilst identifying opportunities to use data science/engineering techniques to extract value from internal/external data assets in order to enrich analytical capabilities.
If you are looking for a role in which you can utilise your capability of statistical techniques, such as regression, clustering, correlation analysis, then this could be the role for you.
Our culture
Inclusion & Diversity is at the heart of our business at Ki. We recognise that diversity in age, race, gender, ethnicity, sexual orientation, physical ability, thought and social background bring richness to our working environment. No matter who you are, where you’re from, how you think, or who you love, we believe you should be you.
You’ll get a highly competitive remuneration and benefits package. This is kept under constant review to make sure it stays relevant. We understand the power of saying thank you and take time to acknowledge and reward extraordinary effort by teams or individuals.
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Data Analyst employer: Ki Insurance
Contact Detail:
Ki Insurance Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Familiarise yourself with the latest trends in data analytics and insurance technology. Understanding how companies like Ki are leveraging data to revolutionise the industry will give you an edge in interviews.
✨Tip Number 2
Showcase your experience with BI tools and Python by preparing a portfolio of relevant projects. Highlight any dashboards or data visualisations you've created that demonstrate your ability to meet business requirements.
✨Tip Number 3
Network with professionals in the insurance tech space, especially those involved in data analytics. Engaging with industry experts can provide insights into the role and may even lead to referrals.
✨Tip Number 4
Prepare to discuss statistical techniques like regression and clustering during your interview. Be ready to explain how you've applied these methods in past projects to extract valuable insights from data.
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities of a Data Analyst at Ki. Familiarise yourself with the specific skills mentioned in the job description, such as experience with BI tools and Python, as well as statistical techniques like regression and clustering.
Tailor Your CV: Customise your CV to highlight relevant experience and skills that align with the job requirements. Emphasise your background in data visualisation, analytics, and any projects where you've successfully used statistical techniques.
Craft a Compelling Cover Letter: Write a cover letter that not only showcases your qualifications but also reflects your enthusiasm for Ki's mission and culture. Mention how your values align with their focus on inclusion and diversity, and express your eagerness to contribute to their digitisation efforts.
Proofread and Edit: Before submitting your application, carefully proofread all documents for spelling and grammatical errors. A polished application demonstrates attention to detail, which is crucial for a role that involves data analysis.
How to prepare for a job interview at Ki Insurance
✨Showcase Your Technical Skills
As a Data Analyst, you'll need to demonstrate your proficiency in tools like Python and modern BI platforms. Be prepared to discuss specific projects where you've built dashboards or conducted data analysis, highlighting the techniques you used and the impact of your work.
✨Understand the Company’s Mission
Ki is focused on revolutionising the insurance industry through digitisation. Familiarise yourself with their goals and how your role as a Data Analyst can contribute to this mission. This shows your genuine interest in the company and its objectives.
✨Prepare for Technical Questions
Expect questions related to statistical techniques such as regression, clustering, and correlation analysis. Brush up on these concepts and be ready to explain how you've applied them in real-world scenarios, as this will demonstrate your analytical capabilities.
✨Emphasise Collaboration and Communication
Since you'll be working with various teams, highlight your experience in collaborative environments. Discuss how you’ve effectively communicated complex data insights to non-technical stakeholders, showcasing your ability to foster a data-driven decision-making culture.
