Arthur Recruitment
Data Analyst - Insurance Broking

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Data Analyst, Insurance Broking
London | Hybrid
60K
Arthur is partnering with a leading global insurance broker to appoint an experienced Data Analyst into its growing analytics function.
This is a highly technical and commercially focused role, working closely with brokers and insurance professionals to transform complex insurance datasets into meaningful insight. You’ll have the opportunity to work across data analytics, Python engineering, automation, data quality and visualisation, helping improve how data is used to support client and placement decisions.
The Role
You’ll work as part of a specialist analytics team, partnering closely with brokers and other stakeholders to understand their data requirements and deliver high quality analysis.
Key responsibilities will include:
- Analyse large and complex insurance datasets, providing insight across claims experience, loss ratios, exposure, portfolio performance and market trends
- Work closely with brokers and stakeholders to provide data driven insight supporting client and placement decisions
- Design, build and optimise Python data pipelines to ingest, cleanse, transform and standardise data from multiple sources
- Use Python, Pandas, SQL and modern development practices to create efficient, repeatable and auditable analytical processes
- Develop automated data quality checks, controls and validation processes to improve the accuracy and reliability of data
- Support the development of centralised exposure, claims and portfolio databases, including relational database and schema design
- Build analytical tools, dashboards and benchmarking datasets to compare portfolios across clients, classes of business and different time periods
- Identify opportunities to automate manual processes and improve the efficiency of existing analytics workflows
- Produce clear and engaging visualisations and reporting using Power BI, Excel and Power Query
- Explore emerging technologies across Data, Analytics, Automation and AI and how they can be applied within insurance broking
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
About You
We’re looking for someone who combines strong technical data capabilities with an understanding of the insurance market.
You’ll ideally bring:
- 3+ years’ experience within a Data Analyst, Senior Data Analyst or similar analytics role
- Previous experience within Insurance, Reinsurance, Insurance Broking or the London Market
- Strong Python skills, particularly Pandas, data cleansing, transformation and automation
- Strong SQL skills with experience working with relational databases and data models
- Experience working with large, complex and inconsistently structured datasets
- Experience building or maintaining data pipelines and automated analytical processes
- Strong understanding of data quality, validation and controls
- Experience with Git, GitHub and collaborative development practices
- Strong Power BI, Excel and Power Query capabilities
- Understanding of insurance datasets such as claims, exposure, loss, premium and portfolio data
- Exposure to reinsurance and casualty insurance would be particularly advantageous
- Strong communication skills with the ability to translate technical analysis into clear commercial insight for non technical stakeholders
- Understanding of data governance and regulatory requirements, including GDPR


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