This role has closed. Hyperiongrp has taken the posting down.
hirly last saw it live on 16 October 2026. See similar open roles below, or browse all Data Analyst jobs in London.
Hyperiongrp
Data Analyst - Specialty
London
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hirly's read of this role
- Seniority
- Mid level
- Country
- GB
- Work mode
- On-site / unstated
- First seen by hirly
- 12 Oct 2026
Derived automatically from the posting.
the posting
Who are we?
Howden is a global insurance group with employee ownership at its heart. Together, we have pushed the boundaries of insurance. We are united by a shared passion and no-limits mindset, and our strength lies in our ability to collaborate as a powerful international team comprised of 24,000 employees spanning over 56 countries.
People join Howden for many different reasons, but they stay for the same one: our culture. It’s what sets us apart, and the reason our employees have been turning down headhunters for years. Whatever your priorities – work / life balance, career progression, sustainability, volunteering – you’ll find like-minded people driving change at Howden.
Role Purpose
We’re looking for a curious, analytical early-career data analyst to support our Aviation team. This is a hands-on role where you’ll learn how data drives business decisions — turning complex datasets into clear insights that support clients and the business across Aviation.
You don’t need deep aviation knowledge on day one. Strong data foundations, curiosity and the motivation to learn fast matter most; the aviation context can be picked up on the job. With support and mentoring from experienced analysts, you’ll grow into a role that combines data analysis, reporting and the use of AI to optimise how the team works.
Role Overview
The role is dedicated to the Aviation team. Its primary focus is to support Emma Roberts (Senior Data Analyst, Aviation) and, through her, the wider Aviation team with data analysis, reporting and analytics; all of the role’s deliverables relate to the aviation portfolio.
For the first year, the role will report to Anna Bordon (Head of Specialty Insights and Analytics) and spend approximately 25% of each week embedded with the central Data & Analytics team. That team provides the formal training, tooling and access to the “back end” — the data lake, SQL and detailed data-analytical environment — that sits behind the Aviation team’s reporting, and the role applies that capability directly to Aviation work.
The Aviation team’s data function is currently led by deep domain knowledge — over 20 years of aviation insurance experience across claims, finance, broking and account management — together with a clear understanding of the data and the outputs the team needs. This role complements that domain expertise with formal analytical and technical depth (data-lake access, SQL and structured data analysis), developed and supported through the Data & Analytics team.
In summary:
Focus: dedicated to Aviation team data, reporting and analytics.
Reporting line (first year): Anna Bordon, Head of Specialty Insights and Analytics.
Working pattern: approximately 25% of each week embedded with the Data & Analytics team.
Development model: technical training, tooling and back-end (data lake / SQL) access provided by the Data & Analytics team and applied directly to Aviation work.
What You’ll Do
Work with brokers and business stakeholders to understand real-world problems and translate them into data and AI questions.
Explore and prototype data ideas, helping to shape user stories and analytical approaches.
Clean, analyse and validate data from multiple sources — including premium and placement data, claims experience and underwriter / portfolio performance — to ensure accuracy and reliability.
Spot patterns, trends and anomalies, and help explain what they mean in practice.
Use modern data and analytics tools to turn raw data into clear, actionable outputs — reports, dashboards and analytics that support broker lineslips / facilities and senior management, both regular and ad-hoc.
Support the use of AI-enabled tools to automate repetitive data entry, cleansing and reconciliation, and to accelerate the production of reports and analytics.
Collaborate with data, technology and analytics teams across the wider group.
Apply appropriate human review, document your work and follow best-practice data and AI standards. Break problems into steps an agent can execute, and use good judgement about when to lean on AI and when to do the work yourself.
What You’ll Grow Into
As you build aviation domain knowledge and technical depth, the role broadens to include:
Acting as a data and analytics point of contact for the team’s lineslip portfolio — building and maintaining reporting suites covering bordereaux, income, claims and utilisation.
Producing consolidated, portfolio-level analytics to support renewal strategy and market presentations.
Identifying data-quality issues in lineslip records and working with brokers to resolve them at source.
Acting as a business-analyst liaison between the broking team and IT / AI development resources — defining requirements, mapping workflows and setting data-capture standards.
Participating in testing (UAT) and supporting brokers using AI-enabled tools: troubleshooting, onboarding users and maintaining guides and training materials.
What We’re Looking For
Essential
A degree (or equivalent) in a numerate or analytical subject — e.g. maths, statistics, data science, economics, engineering or sciences.
Strong attention to detail and logical thinking.
A genuine interest in how data can influence business decisions.
Confidence explaining ideas to both technical and non-technical audiences.
An inquisitive, problem-solving mindset — comfortable with modern AI tooling and keen to keep pace with a fast-moving landscape.
Technical skills (you don’t need all of these on day one)
Experience using Excel for analysis.
Exposure to Python, SQL and/or R through study, projects or internships.
Familiarity with data-visualisation tools such as Power BI (or similar).
Interest in learning modern data platforms (e.g. Databricks).
Experience using GenAI / LLMs to support operational workflows and analytics.
Any exposure to automation tools (e.g. Power Automate) and to producing presentation materials is an advantage.
Nice to have (but not required)
University or personal projects involving real datasets.
A basic understanding of data modelling or data pipelines.
An interest in — or willingness to learn — insurance and aviation. Domain knowledge can be developed on the job.
Key Stakeholders
Emma Roberts and the wider Aviation team.
Aviation brokers and client executives.
Markets / insurers (indirectly, through placement data and reporting).
Central Data & Analytics team; IT / AI development teams.
Operations teams.
How Success Will Be Measured
Accuracy and timeliness of reporting.
Quality and usefulness of data insights.
Data quality and completeness across the aviation portfolio.
Growing confidence and independence with the data platform and analytical tooling.
Adoption and effectiveness of AI-enabled tools in day-to-day work.
Progress against agreed learning and development goals.
Tools & Systems (Typical)
Microsoft Excel.
Power BI.
SQL / data lake (e.g. Databricks).
Power Automate / Power Platform.
SharePoint / Dataverse
GenAI tools (e.g. Copilot / Claude) for reporting and process support.
What You’ll Get
A structured early-career role with on-the-job learning and mentoring.
Exposure to client and operations work across a specialist line of business.
Training and professional qualifications (e.g. Chartered Insurance Institute).
Competitive salary, generous pension and private medical cover.
What do we offer in return?
A career that you define. At Howden, we value diversity – there is no one Howden type. Instead, we’re looking for individuals who share the same values as us:
Our successes have all come from someone brave enough to try something new
We support each other in the small everyday moments and the bigger challenges
We are determined to make a positive difference at work and beyond
Reasonable adjustments
We're committed to providing reasonable accommodatio
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