Technical Pricing Manager – 29170

The Emerald Group; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

The Emerald Group in London is seeking a hands-on Non-life Actuarial professional to build high-quality risk models estimating frequency, severity and pure premium. You will lead the end-to-end modelling lifecycle, perform data cleansing, feature engineering and validation, and collaborate with Portfolio, Reserving and Underwriting.

You will use GLMs, GAMs and modern ML (XGBoost/CatBoost) in R and Python, maintain documentation, ensure governance and audit trails, and translate models into

Qualifications

• Experience with GLMs (Poisson/NB/Tweedie), GAMs, credibility/hierarchical methods; tree-based ML and regularisation.
• Hands-on experience taking models from concept to live in rating engines; robust validation and change control.
• Knowledge of model risk management, documentation standards and governance under UK regulation (Consumer Duty, Fair Value Assessments, GIPP).

Responsibilities

• Own the end-to-end modelling lifecycle: problem framing, data build, feature engineering, model development, validation, documentation
• Build and maintain risk and price models using GLMs and machine learning
• Translate models into implementable rating structures
• Strong governance: change control, champion–challenger/shadow runs, rollback plans, and clear approvals and audit trails
• Strong general insurance pricing toolkit: GLMs (Poisson/NB/Tweedie), GAMs, credibility/hierarchical methods; experience with tree-based ML (GBM/XGBoost/CatBoost) and regularisation
• Proficient in R and Python, with strong SQL; comfortable in Git-based workflows and “in the engine room” with proprietary rating systems
• Hands-on experience taking models from concept to live in rating engines; robust validation, change control and post-live monitoring
• Familiarity with peril/exposure enrichment relevant to home insurance (e.g. flood and subsidence datasets) and geospatial modelling considerations
• Awareness of reserving concepts, claims inflation and their interaction with technical pricing
• Knowledge of model risk management, documentation standards and governance under UK regulation (Consumer Duty, Fair Value Assessments, GIPP)

Skills

Risk modelling

GLMs

Machine learning

Python

R

SQL

Model validation

Governance

Rating engines

Data cleansing

Tools

XGBoost

CatBoost

GBM

GAMs

Git

SQL

Job description

The purpose of this role is to build high-quality risk models that estimate risk costs (frequency, severity and pure premium) as accurately as possible using state-of-the-art techniques. Ensure rigorous data cleansing and preparation, validate model outputs against financial results and portfolio performance, produce comprehensive documentation, and actively incorporate feedback from key stakeholders (Portfolio, Reserving and Underwriting) to refine and maintain models.

• Location: London/ Hybrid working
• Category: Non-life Actuarial
• Type: Permanent

Key Responsibilities (including but not limited to):

• Own the end-to-end modelling lifecycle: problem framing, data build, feature engineering, model development, validation, documentation
• Build and maintain risk and price models using GLMs and machine learning
• Translate models into implementable rating structures
• Strong governance: change control, champion–challenger/shadow runs, rollback plans, and clear approvals and audit trails
• Strong general insurance pricing toolkit: GLMs (Poisson/NB/Tweedie), GAMs, credibility/hierarchical methods; experience with tree-based ML (GBM/XGBoost/CatBoost) and regularisation
• Proficient in R and Python, with strong SQL; comfortable in Git-based workflows and “in the engine room” with proprietary rating systems
• Hands-on experience taking models from concept to live in rating engines; robust validation, change control and post-live monitoring
• Familiarity with peril/exposure enrichment relevant to home insurance (e.g. flood and subsidence datasets) and geospatial modelling considerations
• Awareness of reserving concepts, claims inflation and their interaction with technical pricing
• Knowledge of model risk management, documentation standards and governance under UK regulation (Consumer Duty, Fair Value Assessments, GIPP)