Data Scientist
Description
Verisk is a global data, analytics, and technology company helping organizations make better decisions about risk.
Across the insurance industry, our data, predictive models, and technology support decisions throughout the insurance lifecycle, from underwriting and pricing to claims management and fraud detection. We work with complex, high-value datasets including weather, property, business, financial, claims, policy, medical, imagery, and geodemographic data.
Within Verisk Claims UK, we focus on helping insurers improve how claims are assessed, managed, and resolved. Our analytics and automation solutions help streamline claims processes, identify fraud, and support better outcomes for insurers and their customers.
About the role
We’re looking for an early-career Data Scientist to join our International Analytics Team and help build the next generation of analytics products across claims and underwriting.
This is a role where you can do more than develop models in isolation. You’ll work with real-world insurance data, explore complex problems, test different approaches, and help take models from initial idea through to production.
The work is varied. Depending on the project, you could be developing supervised machine learning models, exploring clustering techniques, working with language models or network analysis, or contributing to AI solutions involving automated document processing, agentic decision-making workflows, and claims analysis and auditing.
You’ll have room to experiment, learn, and build your technical depth while working alongside experienced colleagues who value peer review, knowledge sharing, and high-quality analytical work.
For someone at the beginning of their data science career, this is an opportunity to develop broad, practical experience within a global organization while seeing the real-world impact of your work.
This position can be based in our offices in London or Norwich.
Why join Verisk Claims?
This role offers the combination of technical variety, meaningful data, and long-term career development that can be difficult to find in an early-career data science position.
You’ll be working on products that support real decisions across the insurance industry, with access to diverse datasets and opportunities to apply both established modeling techniques and newer areas of AI.
You’ll also have the scale and stability of Verisk behind you, alongside the opportunity to take genuine ownership of your work, develop your technical expertise, and understand how high-quality data science moves from experimentation into products used by the industry.
If you’re looking for a Data Scientist role where you can keep learning while building things that have a practical, measurable purpose, we’d like to hear from you.
#LI-SD2 #LI-Hybrid
• Support the development of new analytics products for insurance claims and underwriting.
• Explore complex datasets and turn them into meaningful insights, including data processing, cleaning, joining multiple data sources, feature engineering, analysis, and interpretation.
• Build and compare predictive models using techniques such as GLMs, gradient boosting, Random Forests, and neural networks.
• Identify the features and factors that provide meaningful predictive value and understand how they influence model performance.
• Help create, test, and monitor agentic AI workflows that are traceable, repeatable, and suitable 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 and creating functions and templates that can be applied efficiently to future projects.
• Communicate analytical approaches, progress, findings, and recommendations clearly to both technical and non-technical colleagues.
• Take part in peer reviews, sharing ideas and learning from colleagues while contributing to consistently high-quality work.
You don’t need to arrive knowing everything about insurance. We’re looking for someone with strong analytical foundations, curiosity, and the motivation to develop.
Ideally, you’ll bring:
• A bachelor's, master's, or PhD in mathematics, statistics, data science, computer science, another scientific discipline, or a related analytical field.
• 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, with the ability to approach complex questions in a structured way.
• Good attention to detail and an interest in producing reliable, reproducible analytical work.
• Clear written and verbal communication skills, including the ability to explain technical work to different audiences.
• A collaborative approach and willingness to learn from, and contribute to, the wider team.