Senior Data Analyst - AI-Driven Insurance Pricing

Quantiphi; Greater London; On-site; GBP 70,000 - 110,000; Full time

Job summary

Quantiphi in London is seeking a Senior Data Analyst to support delivery of Pricing & Exposure data initiatives. This hands-on role focuses on analyzing complex insurance datasets, translating business needs into data requirements, and producing mapping, profiling and quality evidence to build trusted data products.

You will collaborate with pricing, underwriting, exposure management, data engineering and technology teams to bring structure to ambiguous data, validate source-to-target decisions,

Qualifications

• Substantial experience in a senior data analyst, data-focused business analyst or comparable role.
• Profile pricing, delegated authority and exposure data sources to understand structure, completeness, quality, lineage and suitability for reporting and analytics.
• Analyse conceptual, logical and physical data models against agreed business, reporting and analytical use cases, including data grain, relationships, definitions and business rules.
• Own detailed source-to-target mapping, documenting source fields, target fields, transformations, derivations, reference data, assumptions and traceability to requirements.
• Produce and maintain mapping artefacts, data dictionaries, business glossaries and lineage documentation for use by engineering, testing and business teams.
• Define and run data quality checks, reconcile source and target datasets, investigate material differences and document issues for resolution.
• Identify gaps, inconsistencies and design risks through data analysis, and use findings to inform delivery priorities, data design and remediation activity.
• Support workshops and working sessions alongside existing Business Analysts to capture requirements, validate findings, resolve data questions and align decisions across business and technology teams.
• Translate complex data detail into clear requirements, recommendations and delivery artefacts for technical and non-technical audiences.

Responsibilities

• Substantial experience in a senior data analyst, data-focused business analyst or comparable role.
• Profile pricing, delegated authority and exposure data sources to understand structure, completeness, quality, lineage and suitability for reporting and analytics.
• Analyse conceptual, logical and physical data models against agreed business, reporting and analytical use cases, including data grain, relationships, definitions and business rules.
• Own detailed source‑to‑target mapping, documenting source fields, target fields, transformations, derivations, reference data, assumptions and traceability to requirements.
• Produce and maintain mapping artefacts, data dictionaries, business glossaries and lineage documentation for use by engineering, testing and business teams.
• Define and run data quality checks, reconcile source and target datasets, investigate material differences and document issues for resolution.
• Identify gaps, inconsistencies and design risks through data analysis, and use findings to inform delivery priorities, data design and remediation activity.
• Support workshops and working sessions alongside existing Business Analysts to capture requirements, validate findings, resolve data questions and align decisions across business and technology teams.
• Translate complex data detail into clear requirements, recommendations and delivery artefacts for technical and non-technical audiences.

Skills

Advanced SQL

Data profiling

Data mapping

Data modeling

Documentation

Communication

Independent work

Attention to detail

Tools

Microsoft Fabric

Job description

Quantiphi in London is seeking a Senior Data Analyst to support delivery of Pricing & Exposure data initiatives. This hands-on role focuses on analyzing complex insurance datasets, translating business needs into data requirements, and producing mapping, profiling and quality evidence to build trusted data products.

You will collaborate with pricing, underwriting, exposure management, data engineering and technology teams to bring structure to ambiguous data, validate source-to-target decisions,