Lead Underwriting Data Scientist – Portfolio Analytics

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

Benefits offered by this job

10% discretionary bonus

Annual pay reviews

Up to 22 work from anywhere days

Private medical cover

Critical illness insurance

Employer pension matching up to 7.5%

25 days holiday, 30 with tenure, plus

2 my time days

£300 WFH setup budget

EV scheme + cycle to work

Market-leading parental leave

Dedicated learning and training budget

Job summary

Skillful is seeking an underwriting analytics professional in the UK to refine analytical logic used by underwriters across coverage, rates and portfolio footprint. You will split time between heads-down analysis and leading projects, helping shape live decisions on quotes and policies.

Your background in underwriting analytics, pricing, or data science will be crucial. Proficiency in Python or R and SQL is required, with GBMs and fraud analytics as strong assets.

Qualifications

• Experience in underwriting analytics, pricing, or data science within insurance.
• Ability to build and deploy models that influence live underwriting decisions.
• Strong communication with senior stakeholders to explain complex findings.
• Proficiency in Python or R and SQL.

Responsibilities

• Analyse portfolio performance and adjust coverage, rates, or footprint.
• Develop fraud detection models and new risk signals at quote.
• Collaborate with underwriters to improve risk assessment and decision making.
• Translate complex findings for senior stakeholders and non-technical audiences.
• Deploy models into production to influence live underwriting decisions.
• Mentor junior analysts and share technical knowledge.

Skills

Python

R

SQL

GBM modelling

Fraud analytics

Data enrichment

Tools

BigQuery

Azure

Job description

Skillful is seeking an underwriting analytics professional in the UK to refine analytical logic used by underwriters across coverage, rates and portfolio footprint. You will split time between heads-down analysis and leading projects, helping shape live decisions on quotes and policies.

Your background in underwriting analytics, pricing, or data science will be crucial. Proficiency in Python or R and SQL is required, with GBMs and fraud analytics as strong assets.