At a Glance
- Tasks: Lead data analysis and drive growth in the fast-paced InsurTech sector.
- Company: Join a dynamic InsurTech company revolutionising the UK motor insurance market.
- Benefits: Enjoy a hybrid work model, competitive salary, and generous holiday allowance.
- Why this job: Make a real impact by bridging traditional underwriting with innovative data science.
- Qualifications: Experience in UK General Insurance and proficiency in SQL and Python required.
- Other info: Collaborative culture with excellent career development opportunities.
The predicted salary is between 36000 - 60000 ÂŁ per year.
Location: Hybrid in-office 2 days per week. Mainly in our Fleet (Hampshire) office, with option to work in our office in London (Tower Bridge).
Tempcover is at the forefront of the fast‑growing, high‑volume short‑term UK motor insurance market. Our mission is to make car insurance flexible, quick, and easy. We seek an extraordinary analytical leader to join our rapidly growing InsurTech business and drive the next phase of profitable growth. The Lead Underwriting Analyst is a critical, hands‑on role (70% individual contributor, 30% project/people management). You will bridge traditional underwriting principles with cutting‑edge data science, designing and deploying automated underwriting logic and sophisticated algorithms to help our panel of underwriters achieve targeted loss ratios on high‑volume, short‑term UK motor policies (one hour to one month).
Key Responsibilities
- Drive growth through expanding our footprint and optimising rates, considering profitability and risk in every initiative, monitoring and refining to maximise potential.
- Use advanced modelling techniques to support the prevention of fraud and the advancing identification of risk.
- Utilise immediate data enrichment and non-traditional data sources (e.g external validation services) to identify new signals for risk selection and fraud identification at point of quote.
- Monitor critical key performance indicators (KPIs), highlighting movements and recommending action where necessary.
- Conduct deeper analysis to support product evolvement, both for core products and new opportunities.
- Manage regulatory compliance, ensuring all underwriting strategies adhere to UK regulatory bodies (e.g FCA) guidelines for fairness, transparency, and data usage.
- Work closely with Engineering and Product teams to translate complex models into scalable, production decision engines.
- Line‑manage and formally mentor junior analysts, focusing on their technical development, project allocation, and best practices.
Skills, Knowledge and Expertise
- Experience in the UK General Insurance market, with strong preference for experience in high frequency Motor Insurance products.
- Proven track record of building, implementing, and optimising profitable underwriting strategies.
- Expert‑level proficiency in SQL for rapid data extraction and manipulation from large datasets.
- Advanced skills in a statistical programming language (Python or R) for modeling, data transformation, and visualisation.
- Strong experience with visualisation and reporting tools such as PowerBI and/or Tableau.
- Experience with cloud-based data warehouses (e.g. BigQuery or Azure) is highly desirable for processing real‑time risk data.
- Familiarity with machine learning concepts and their application in insurance, particularly in real‑time scoring and fraud detection.
- Familiarity with the WTW insurance software RADAR is desirable but not essential.
- Excellent communication skills, with the ability to articulate complex analytical findings and regulatory compliance impacts to non-technical stakeholders.
- Strong commercial acumen and the ability to balance strict risk control with high-speed customer experience in a competitive InsurTech environment.
- Collaborative mindset, keen to support others and learn from them.
- Pragmatic and focused on finding actionable insights.
You don’t need to tick off everything on this list - so don’t let that hold you back from applying. We want to make sure you’re learning plenty during your time with us!
Benefits
- 10% discretionary yearly bonus and yearly pay reviews (based on RVU and personal performance).
- A hybrid working approach with 2 in-office days per week and up to 22 working days per year to “work from anywhere”.
- Employer matching pension contributions up to 7.5%.
- A one-off £300 “Work from Home” budget to help contribute towards a great work environment at home.
- Excellent maternity, paternity, shared parental and adoption leave policy, for those key moments in your life.
- 25 days holiday (increasing with years of employment to 30 days) + 2 days “My Time” per year.
- Private medical cover, critical illness cover and employee assistance programme.
- A healthy learning and training budget.
- Electric vehicle and cycle to work schemes.
- Regular events - from team socials to company‑wide events with insightful external speakers, we want to make sure our colleagues continue to feel connected.
Lead Data Analyst in Fleet employer: RVU Co UK
Contact Detail:
RVU Co UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Analyst in Fleet
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend events, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your analytical skills. Use real-life examples from your experience to demonstrate how you've tackled challenges in data analysis and underwriting.
✨Tip Number 3
Don’t just apply and wait! Follow up on your applications with a friendly email. It shows your enthusiasm and keeps you on their radar. Plus, it’s a great way to ask if they need any more info from you.
✨Tip Number 4
Check out our website for the latest job openings and apply directly. We love seeing candidates who are proactive and genuinely interested in joining our team at Tempcover!
We think you need these skills to ace Lead Data Analyst in Fleet
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the Lead Data Analyst role. Highlight your experience in the UK General Insurance market and any relevant skills like SQL and Python. We want to see how your background aligns with our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about InsurTech and how you can contribute to our growth. Be sure to mention specific projects or achievements that showcase your analytical prowess.
Show Off Your Analytical Skills: In your application, don’t just list your skills—demonstrate them! Share examples of how you've used advanced modelling techniques or data visualisation tools to drive results. We love seeing real-world applications of your expertise.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you get all the updates. Plus, it’s super easy to do!
How to prepare for a job interview at RVU Co UK
✨Know Your Data Inside Out
As a Lead Data Analyst, you'll need to demonstrate your expertise in SQL and statistical programming languages like Python or R. Brush up on your skills and be ready to discuss specific projects where you've used these tools to drive insights or optimise strategies.
✨Showcase Your Analytical Mindset
Prepare to talk about how you've applied advanced modelling techniques in previous roles, especially in the context of fraud prevention and risk identification. Use examples that highlight your ability to translate complex data into actionable insights.
✨Understand the InsurTech Landscape
Familiarise yourself with the UK General Insurance market, particularly high-frequency motor insurance products. Be ready to discuss current trends and how they might impact underwriting strategies, showing that you’re not just a number cruncher but also a strategic thinker.
✨Communicate Clearly and Confidently
Since you'll be working with non-technical stakeholders, practice explaining your analytical findings in simple terms. Think of ways to convey complex concepts clearly, as this will demonstrate your excellent communication skills and collaborative mindset.