Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Analyst

Hiscox
City of London
6 days ago
Create job alert

Job Type:PermanentBuild a brilliant future with HiscoxPosition: Data AnalystReporting to: Analytics Development ManagerLondon Or York - Hybrid - min 1 day per week in the officeThe TeamGroup Enterprise Systems (GES) is a central technology function within Hiscox responsible for delivering and supporting enterprise-wide systems and services. It plays a strategic role in enabling business operations through scalable, secure, and cost-effective technology platforms. GES supports to five business-aligned Technology teams partnering with our federated business units. Collectively the goal of the Technology organisation is to put Technology at the heart of the business.You'll be working in a team of Business Analysts, Data Analysts, Data Engineers and Analytics Engineers within a specialised Group Data Engineering Team. We are all working towards the same goal: Enabling the generation of data driven insights for business stakeholders.The RoleWe are looking for an expert in data analysis to interrogate and build subject matter expertise in our enterprise data warehouse ecosystems. The role requires ‘hands on’ investigation of complex insurance data, you’ll collaborate with business stakeholders and fellow technical resources to translate business problems into data driven solutions. You’ll have the opportunity to contribute to high profile group data initiatives and be a part of a dynamic and rapidly expanding data community, with access to leading technologies.Key Responsibilities of a Data Analyst:* Build strong productive relationships with the business, IT teams and external 3rd parties* Analyse Hiscox’s data warehouse ecosystem* Build subject matter expertise in complex enterprise data flows and processes* Act as a liaison for business partners with the ability to translate complex technical challenges into business-friendly information* Assist 3rd Parties to ensure Hiscox regulatory compliance during regular audits* Crafting datasets for use in analysis, reporting and dashboarding* Contribute to the delivery of impactful analytics products like dashboards, visualisations and reports* Documenting of key activities and processes* Provide BAU support to the business during regular financial cyclesMust have skills:* 3 + years experience in a Data Analyst role in Insurance (very desirable). Wider Financial Services experience will be considered* Critical Thinking - ability to interpret data and identify patterns, trends, and anomalies and make reasoned judgements.* Problem Solving - apply logical reasoning to break down complex issues into smaller components* High level of ability in SQL* Strong understanding of data modelling concepts* Confident communicator with both technical and non-technical audiences* Strong attention to detail* Experience with data engineering tools like SSIS, Azure Data Factory or similar* Experience working in an Agile environment* Understanding of DevOps principles and experience applying them* Exposure to business intelligence, data engineering and data visualisation concepts* Exposure to modern analytics platforms like Tableau/ Power BI / Fabric* Ability to elicit requirements. Such as user stories, acceptance criteria, functional & non-functional specifications, business casesNice to have skills:* Experience using Databricks in an enterprise environment* Experience coding with Python* Exposure to ML Ops* Degree in Science, Computer Science, Mathematics or similar quantitative discipline* Analytics vendor certification**About Hiscox:**As an international specialist insurer we are far removed from the world of mass market insurance products. Instead we are selective and focus on our key areas of expertise and strength - all of which is underpinned by a culture that encourages us to challenge convention and always look for a better way of doing things.We insure the unique and interesting. And we search for the same when it comes to talented people. Hiscox is full of smart, reliable human beings that look out for customers and each other. We believe in doing the right thing, making good and rebuilding when things go wrong. Everyone is encouraged to think creatively, challenge the status quo and look for solutions.Scratch beneath the surface and you will find a business that is solid, but slightly contrary. We like to do things differently and constantly seek to evolve. We might have been around for a long time (our roots go back to 1901), but we are young in many ways, ambitious and going places.Some people might say insurance is dull, but life at Hiscox is anything but. If that sounds good to you, get in touch.#LI-AS1#LI-HybridWork with amazing people and be part of a unique cultureIf you want to help build a brilliant future; work with amazing people; be part of a unique company culture; and, of course, enjoy great employee benefits that take care of your mental and physical wellbeing, come and join us.
#J-18808-Ljbffr

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.