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- Tasks: Analyse data to drive performance and improve customer outcomes in the insurance sector.
- Company: High-growth insurance business focused on data-driven decision making.
- Benefits: Competitive salary, hybrid working, and a comprehensive benefits package.
- Other info: Collaborative environment with opportunities for professional development.
- Why this job: Make a real impact by translating data into actionable insights for growth.
- Qualifications: Experience as a Data Analyst with strong SQL and data visualisation skills.
The predicted salary is between 45000 - 55000 £ per year.
We are supporting a high-growth, performance-led business in the insurance sector as they continue to scale their data capability. This is a role for a commercial Data Analyst - someone who can go beyond reporting and play a meaningful role in improving conversion, customer outcomes and revenue performance. You will report into the Chief Growth Officer and work closely with marketing, sales and operations to understand what is driving performance, where opportunities exist, and how data can be used to improve outcomes across the business.
Key Responsibilities
- Analyse customer, lead and sales data to identify trends, insights and performance drivers - working closely with the sales leadership team
- Develop insights across operational and colleague performance, funnel and trading insights, building agent performance reports and dashboards to track KPIs
- Support optimisation of conversion across the customer journey (lead → sale)
- Evaluate campaign performance, channel effectiveness and ROI
- Partner with stakeholders to understand business challenges and provide actionable insight
- Support testing and experimentation (A/B testing, funnel optimisation)
- Translate data into clear, commercially relevant recommendations
Skills & Experience Profile
- Experience in a Data Analyst role within a commercial or performance-driven environment
- Strong SQL skills and experience working with large datasets
- Experience with data visualisation tools (Power BI, Tableau or similar)
- Ability to translate data into meaningful business insight
- Experience working with non-technical stakeholders
Desirable
- Marketing or sales analytics (funnels, conversion, attribution)
- Experience in insurance, financial services or high-volume B2C environments
- Exposure to experimentation / A/B testing
- Python or R
Additional Information
- Salary: £45,000 - £55,000 (based on experience) + benefits package
- Location: Hybrid working with onsite travel to the office in Berkshire. Candidates must have the right to work and reside in the UK.
Data Analyst - Financial Services in London employer: Shareforce
Contact Detail:
Shareforce Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst - Financial Services in London
✨Tip Number 1
Network like a pro! Reach out to people in the insurance and financial services sectors. Use LinkedIn to connect with current employees at companies you're interested in. A friendly chat can sometimes lead to job opportunities that aren't even advertised!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data analysis projects, especially those involving SQL and data visualisation tools like Power BI or Tableau. This will give potential employers a taste of what you can do and how you can add value to their team.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of A/B testing and conversion optimisation. Be ready to discuss how you've used data to drive business decisions in the past. We want to see your analytical thinking in action!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to engage directly with us. Let’s get you that Data Analyst role!
We think you need these skills to ace Data Analyst - Financial Services in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Data Analyst in Financial Services. Highlight your experience with SQL, data visualisation tools, and any relevant projects that showcase your ability to drive performance and insights.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've used data to improve customer outcomes or conversion rates in previous roles. Make it personal and engaging!
Showcase Your Analytical Skills: In your application, don’t just list your skills—demonstrate them! Include examples of how you've analysed data to identify trends or improve performance. We want to see your thought process and how you approach problem-solving.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Shareforce
✨Know Your Data Inside Out
Make sure you’re familiar with the types of data you’ll be working with. Brush up on your SQL skills and be ready to discuss how you've used data to drive business decisions in the past. Prepare examples that showcase your ability to analyse customer and sales data effectively.
✨Showcase Your Visualisation Skills
Since data visualisation is key for this role, be prepared to talk about your experience with tools like Power BI or Tableau. Bring along a portfolio of dashboards or reports you've created, and be ready to explain how they helped improve performance or conversion rates.
✨Understand the Business Context
Research the insurance sector and understand the specific challenges it faces. Be ready to discuss how data can solve these issues and improve customer outcomes. This shows you’re not just a number cruncher but someone who understands the bigger picture.
✨Prepare for Stakeholder Engagement
You’ll need to work closely with non-technical stakeholders, so practice explaining complex data insights in simple terms. Think of examples where you’ve successfully communicated findings to different teams, and be ready to demonstrate your collaborative approach.