Pricing Data Scientist
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:
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Design and implement pricing models using both actuarial and machine learning techniques.
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Perform in-depth analysis of historical data and industry trends to provide strategic recommendations.
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Partner with underwriters by developing tools and models that enhance risk assessment.
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Evaluate pricing performance and identify opportunities for revenue optimisation and margin improvement.
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Champion the integrity and accuracy of pricing data and methodologies.
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Foster a data-driven decision-making culture within the organisation.
Tech Stack & Skills Required:
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Excel (expert level)
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Advanced SQL
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Python for handling and analysing large datasets
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Experience with data science and machine learning methods
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API integration for extracting data from diverse sources
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Strong statistical and analytical mindset
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Proven experience in the insurance sector, specifically pricing
Why Join:
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Work in a progressive environment that actively integrates data science and ML into pricing
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Be part of a dynamic and collaborative team within a well-established insurer
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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 | 2026-11-24 |