Data Analyst

Howden is a global insurance group seeking to build a data-driven US insurance brokerage platform. The Data Analyst will partner with business leaders to develop data models, analytics products, visualizations, forecasting tools, and decision-support solutions, while owning the analytics product lifecycle from exploration through adoption.

Responsibilities:

• Operate as an embedded, trusted business partner who understands business processes, decisions, pain points, desired outcomes, and priorities
• Proactively identify and recommend data and analytics solutions that create measurable business value rather than waiting for formal requests
• Work iteratively to translate business questions and stakeholder conversations into data visualizations, creative calculations, consumption-ready data models, and acceptance criteria
• Use AI capabilities to accelerate data exploration, requirements documentation, SQL development, calculations, visualization, testing, and prototyping
• Create dashboard and data-product mockups in live working sessions for immediate feedback and faster alignment
• Partner with engineering and governance colleagues to build end-to-end data products as ideas move from exploration to industrialization, capturing metric definitions, calculation logic, lineage, ownership, assumptions, and data-quality rules as part of product delivery—establishing standards for functions still taking shape
• Build forecasting, segmentation, and scenario analysis tools that support decision-making
• Profile, validate, and reconcile data against source systems, business expectations, and defined quality rules; investigate and resolve discrepancies
• Own the analytics product lifecycle: understand, prototype, demonstrate, gather feedback, refine, validate, release, and measure adoption

Requirements:

• The ideal candidate combines business curiosity, analytical judgment, technical fluency, data interrogation skills, and a builder's mindset
• You are comfortable working interactively with stakeholders
• You may not be an expert in dimensional modeling, data engineering, data visualization, project management, and context engineering, but you are confident that you can learn what you don't already know
• Strong collaboration skills and the ability to connect priorities to practical data and analytics solutions
• Comfort operating with ambiguity and limited precedent; ability to identify ambiguous business problems, structure them analytically, and translate them into actionable data products
• Strong analytical and commercial judgment, with the ability to evaluate trade-offs and make evidence-based recommendations
• Proficiency with BI tools, data visualization, and SQL, with knowledge of dimensional modeling and medallion architecture
• Experience using AI-assisted capabilities responsibly to accelerate analysis, development, documentation, testing, or prototyping
• Excellent visualization, storytelling, and communication skills across technical and non-technical audiences, including senior leadership
• Bachelor's degree in Analytics, Data Science, Information Systems, Business, Finance, Economics, Statistics, or a related field, or equivalent professional experience
• 3+ years of experience in data analysis, business intelligence, analytics product development, or related discipline
• Demonstrated experience translating business needs into dashboards, analytical products, metrics, or decision-support solutions
• Hands-on experience with SQL and a modern data visualization platform such as Power BI
• Experience working across business and technical teams, including business leaders, subject-matter experts, data engineers, architects, and governance partners
• Demonstrated experience taking an analytics solution from problem definition through prototyping, validation, release, adoption, and ongoing improvement
• Experience with predictive modeling is a plus
• Python or R experience is a plus
• Experience with cloud data platforms, Python, Databricks, or AI-enabled analytics and development tools is preferred
• Insurance brokerage, financial services, or other data-intensive industry experience is preferred
• Experience standing up new analytics capabilities or reporting functions from scratch is preferred