Technical Business Analyst – Underwriting Analytics

Granard Consulting; Greater London; Hybrid; GBP 70,000 - 100,000; Full time

Job summary

Granard Consulting seeks a Technical Business Analyst for Insurance Data, Analytics & AI in London. The role sits at the intersection of underwriting, data and AI, translating complex requirements into data designs and deliverables for client engagements.

You will work hands-on with underwriters and portfolio teams, profile data with SQL and Python, and collaborate with offshore data science and engineering teams to deliver robust solutions.

Qualifications

• 5–8 years as a Business Analyst or Technical BA, with at least 3 years in underwriting, pricing or portfolio analytics within insurance
• Strong understanding of underwriting concepts and workflows in commercial, specialty or personal lines
• Hands-on technical skills across: SQL (advanced) and Python for data profiling and analysis
• BI and visualisation tools (Power BI or Tableau)
• Cloud data platforms (Databricks, Snowflake, Azure, AWS or GCP)
• Process mapping (BPMN / Visio), user stories and source-to-target mapping
• Experience on ML or AI projects, with a practical grasp of model inputs and outputs, explainability, evaluation and human-in-the-loop controls
• Experience working in Agile teams using Jira or Azure DevOps
• Confident communicator who can work equally well with underwriters and engineers
• Experience working with offshore delivery teams
• London Market, Lloyd’s or MGA experience, including delegated authority and bordereaux data
• Familiarity with underwriting and rating platforms (e.g. Guidewire, Duck Creek, Sapiens, Radar, Earnix)
• Experience with third-party enrichment data (e.g. Dun & Bradstreet, Experian, geospatial and catastrophe data)
• Relevant certifications (CII, IIBA CCBA / CBAP, BCS Business Analysis, Agile Product Owner)
• Degree in Mathematics, Statistics, Economics, Computer Science, Engineering or a related field

Responsibilities

• Lead workshops with underwriters, pricing and portfolio management to understand the underwriting lifecycle (submission intake, triage, risk assessment, referral, quote, bind and renewal)
• Document current- and target-state processes, business rules (appetite, referral authorities, rating rules), user stories and acceptance criteria
• Translate business needs into functional and non-functional requirements for analytics, ML and GenAI solutions
• Profile and analyse policy, quote, exposure, claims and third-party data using SQL and Python to test hypotheses and assess data quality
• Produce source-to-target mappings, data dictionaries and KPI definitions (e.g. GWP, loss ratio, rate change, quote and hit ratios, referral and STP rates)
• Define data product requirements and work with data engineers on pipelines and models, keeping scope to what each use case actually needs
• Shape underwriting use cases such as submission triage, risk scoring, pricing adequacy, portfolio monitoring, document extraction and underwriter copilots
• Own and refine the backlog with the client Product Owner, and take an active part in Agile ceremonies
• Define test scenarios, lead UAT with underwriters, and validate model outputs, rules and dashboards against business expectations
• Act as the onshore link to offshore teams: clarify requirements, review outputs and manage hand-offs across time zones
• Support adoption through training material, user guides and tracking of usage and outcome metrics
• Communicate findings, progress and risks clearly to client stakeholders and the engagement lead
• Contribute to discovery phases, proposals and reusable assets (requirement templates, underwriting data models, KPI libraries)

Skills

SQL

Python

Power BI

Tableau

Databricks

Snowflake

Azure

AWS

GCP

BPMN

Visio

Jira

Azure DevOps

ML/AI

Communication

Underwriting

Offshore delivery

Education

Mathematics, Statistics, Economics, Computer Science, Engineering degree

Certifications (CII, IIBA CCBA / CBAP, BCS BA, Agile Product Owner)

Tools

Guidewire

Duck Creek

Sapiens

Radar

Earnix

Job description

Role Title: Technical Business Analyst - Insurance Data, Analytics & AI

Location: London, United Kingdom (4 days a week in the office - hybrid working)

Employment Type: Permanent

Summary of the role:

We are looking for an onshore Technical Business Analyst to sit at the intersection of underwriting, data and AI on client engagements with UK insurers, translating underwriting problems into clear requirements, data designs and solutions that our delivery teams can build.

This is a hands-on, client-facing role. You will work directly with underwriters, underwriting managers and portfolio teams, get into the data yourself, and act as the onshore bridge to our offshore data science and engineering teams.

Key responsibilities:

Business Analysis & Requirements

• Lead workshops with underwriters, pricing and portfolio management to understand the underwriting lifecycle (submission intake, triage, risk assessment, referral, quote, bind and renewal)
• Document current- and target-state processes, business rules (appetite, referral authorities, rating rules), user stories and acceptance criteria
• Translate business needs into functional and non-functional requirements for analytics, ML and GenAI solutions

Data & Technical Analysis

• Profile and analyse policy, quote, exposure, claims and third-party data using SQL and Python to test hypotheses and assess data quality
• Produce source-to-target mappings, data dictionaries and KPI definitions (e.g. GWP, loss ratio, rate change, quote and hit ratios, referral and STP rates)
• Define data product requirements and work with data engineers on pipelines and models, keeping scope to what each use case actually needs
• Shape underwriting use cases such as submission triage, risk scoring, pricing adequacy, portfolio monitoring, document extraction and underwriter copilots

Delivery & Quality

• Own and refine the backlog with the client Product Owner, and take an active part in Agile ceremonies
• Define test scenarios, lead UAT with underwriters, and validate model outputs, rules and dashboards against business expectations
• Act as the onshore link to offshore teams: clarify requirements, review outputs and manage hand-offs across time zones
• Support adoption through training material, user guides and tracking of usage and outcome metrics

Stakeholder & Practice Contribution

• Communicate findings, progress and risks clearly to client stakeholders and the engagement lead
• Contribute to discovery phases, proposals and reusable assets (requirement templates, underwriting data models, KPI libraries)

Qualifications and experience we consider essential:

• 5–8 years as a Business Analyst or Technical BA, with at least 3 years in underwriting, pricing or portfolio analytics within insurance
• Strong understanding of underwriting concepts and workflows in commercial, specialty or personal lines
• Hands-on technical skills across:
• SQL (advanced) and Python for data profiling and analysis
• BI and visualisation tools (Power BI or Tableau)
• Cloud data platforms (Databricks, Snowflake, Azure, AWS or GCP)
• Process mapping (BPMN / Visio), user stories and source-to-target mapping
• Experience on ML or AI projects, with a practical grasp of model inputs and outputs, explainability, evaluation and human-in-the-loop controls
• Experience working in Agile teams using Jira or Azure DevOps
• Confident communicator who can work equally well with underwriters and engineers
• Experience working with offshore delivery teams
• London Market, Lloyd’s or MGA experience, including delegated authority and bordereaux data
• Familiarity with underwriting and rating platforms (e.g. Guidewire, Duck Creek, Sapiens, Radar, Earnix)
• Experience with third-party enrichment data (e.g. Dun & Bradstreet, Experian, geospatial and catastrophe data)
• Relevant certifications (CII, IIBA CCBA / CBAP, BCS Business Analysis, Agile Product Owner)
• Degree in Mathematics, Statistics, Economics, Computer Science, Engineering or a related field