Data Scientist

Verisk

. Support development of analytics products for insurance claims and underwriting .

Posted 10/31/2026full-timeLondon • United KingdomMid-LevelSenior💰 £40,000 - £50,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong analytical skills and programming proficiency in Python and SQL, with a focus on developing predictive models and analytical solutions for insurance claims and underwriting. Capable of communicating complex analytical findings to diverse audiences while maintaining a collaborative and detail-oriented approach.

Highest-signal resume keywords

Predictive ModelingPython ProgrammingSQL ProficiencyStatistical AnalysisData Cleaning

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ProcessingFeature EngineeringGLMsGradient BoostingRandom ForestsNeural NetworksData ManipulationData ValidationMachine LearningAnalytical Solutions

Soft Skills

Problem-SolvingAttention to DetailClear CommunicationCollaborationCuriosity

Tools & Technologies

Version ControlAgentic AI Workflows

Industry Keywords

Insurance ClaimsUnderwritingData ScienceStatistical Modeling

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Support development of analytics products for insurance claims and underwriting
Explore complex datasets through data processing, cleaning, joining multiple data sources, feature engineering, analysis, and interpretation
Build and compare predictive models using GLMs, gradient boosting, Random Forests, and neural networks
Identify features and factors with meaningful predictive value and understand their influence on model performance
Help create, test, and monitor traceable, repeatable agentic AI workflows for real-world use
Work with stakeholders to understand requirements and translate business problems into practical analytical solutions
Write clear, reusable, and well-documented code using version control
Create functions and templates reusable for future projects
Communicate analytical approaches, progress, findings, and recommendations to technical and non-technical colleagues
Participate in peer reviews, share ideas, learn from colleagues, and contribute to high-quality work

Requirements

What you’ll need

Early-career data science profile with strong analytical foundations, curiosity, and motivation to develop
Bachelor's, master's, or PhD in mathematics, statistics, data science, computer science, another scientific discipline, or a related analytical field (ideally)
Solid programming skills, ideally using Python and SQL
Experience working with data, including manipulation, cleaning, validation, and analysis
Exposure to statistical modeling, machine learning, or other predictive techniques
Strong logical and problem-solving skills
Good attention to detail and interest in reliable, reproducible analytical work
Clear written and verbal communication skills, including explaining technical work to different audiences
Collaborative approach and willingness to learn and contribute to the wider team

Benefits

Comp & perks

Competitive compensation package aligned with market benchmarks and individual experience
Eligible roles may include short-term incentive opportunities
Medical coverage
Life insurance
Pension plans
Paid time off in line with local labor laws
Wellness initiatives
Fitness programs
Team-building activities
Career development opportunities
Peer review and knowledge-sharing opportunities