Data Science Actuary (PHD Graduates)

JR United Kingdom; Chester; Remote; GBP 45,000 - 70,000; Full time

Job summary

A leading Personal Lines Insurer is seeking a Data Science Actuary to join their Technical Pricing team in Chester. The role involves applying advanced actuary analyses and utilizing new technologies. This fully remote position offers the chance to enhance model sophistication and employ cutting-edge data science techniques. Ideal candidates will have a PhD or Masters and experience in actuarial pricing.

Qualifications

• PhD/Masters in a research-based subject required.
• Experience in actuarial pricing or statistical modeling.
• Strong background in predictive and machine learning preferred.

Responsibilities

• Build predictive/machine learning models.
• Predict claims/perils for severity.
• Produce reports and presentations for stakeholders.

Skills

Predictive Modeling

Machine Learning

Statistical Analysis

Education

PhD/Masters in a research based subject

Job description

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Data Science Actuary (PHD Graduates), chester

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Client:

Arthur Recruitment

Location:

chester, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Views:

12

Posted:

06.06.2025

Expiry Date:

21.07.2025

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Job Description:

I am working with a leading Personal Lines Insurer who are seeking an individual to join their Technical Pricing team. This team is responsible for specialist actuarial analyses of U/W performance within different products such as Home/Motor.

This role offers the opportunity to use new technologies and be involved in delivering strategic change such as improving the sophistication of models and deploying the latest data science techniques.

This vacancy can be fully remote.

Responsibilities:

• Building predictive/machine learning models
• Predict perils for claims/severity
• Producing reports and presentations to communicate the results of actuarial analyses to key stakeholders

Requirements:

• PhD/Masters in a research based subject
• Experience of actuarial pricing or statistical modelling