Description:
KDR is partnering with a prominent Lloyd’s of London insurer to recruit a Lead Pricing Analyst / Pricing Data Scientist. This exciting opportunity places you within the Pricing and Analytics department, helping to shape data-driven pricing strategies through a blend of actuarial and data science methodologies.
This role is perfect for an analytical individual who combines strong technical skills with a creative mindset for building advanced pricing models. You'll collaborate within a multi-disciplinary team of pricing analysts, catastrophe modellers, and data scientists to create impactful solutions that enhance underwriting decisions and drive profitability.
Key Responsibilities:
Design and implement pricing models using both actuarial and machine learning techniques.
Perform in-depth analysis of historical data and industry trends to provide strategic recommendations.
Partner with underwriters by developing tools and models that enhance risk assessment.
Evaluate pricing performance and identify opportunities for revenue optimisation and margin improvement.
Champion the integrity and accuracy of pricing data and methodologies.
Foster a data-driven decision-making culture within the organisation.
Tech Stack & Skills Required:
Excel (expert level)
Advanced SQL
Python for handling and analysing large datasets
Experience with data science and machine learning methods
API integration for extracting data from diverse sources
Strong statistical and analytical mindset
Proven experience in the insurance sector, specifically pricing
Why Join:
Work in a progressive environment that actively integrates data science and ML into pricing
Be part of a dynamic and collaborative team within a well-established insurer
Excellent opportunity to broaden your technical expertise and learn from experts in catastrophe modelling and analytics
| Organization | Lloyd’s of London Insurer |
| Industry | Insurance Jobs |
| Occupational Category | Pricing Data Scientist |
| Job Location | London,UK |
| Shift Type | Morning |
| Job Type | Full Time |
| Gender | No Preference |
| Career Level | Intermediate |
| Experience | 2 Years |
| Posted at | 2025-04-21 3:18 pm |
| Expires on | 2026-01-06 |