INDUSTRY
OVERVIEW
The insurance industry is undergoing a data analytics revolution. As businesses increasingly rely on data-driven insights to drive decision-making, the demand for data analytics professionals who can provide risk management solutions within the insurance sector is surging.
In recent years, the realm of data and analytics has gained paramount importance, resulting in the emergence of specialized roles such as credit analysts, data scientists, data engineers, and analytics developers. One of the key challenges in Insurance Data Recruitment is identifying individuals with the right skill set to aid their company's risk management services. These positions necessitate expertise in programming languages, data modelling, statistical analysis, and knowledge of advanced data analytics techniques. All whilst working within the organisation's risk management framework, which varies from company to company.
Currently, there exists a notable scarcity of skilled data analytics professionals, rendering it challenging for insurance companies to identify the right talent to fill crucial roles. The demand for skilled professionals in Insurance Data Recruitment is expected to grow in the coming years as the insurance industry continues to evolve. Consequently, a competitive landscape has started to emerge, characterized by escalating salaries and benefits as organizations vie for qualified candidates.
Attracting and retaining top talent through insurance data recruitment insurance companies must cultivate a supportive and innovative workplace culture that nurtures growth, learning, and collaboration. Insurance Data Recruitment is a strategic imperative for these companies. By investing in the recruitment, training and development of their workforce, insurers can secure the retention of skilled professionals and maintain a competitive edge in the data analytics-driven insurance landscape. Contact one of our insurance data recruitment experts today to stay ahead in this evolving industry.
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CORE SKILLS
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Data Analysis: Data analysts in insurance need a strong grasp of data analysis techniques. This involves the ability to clean, preprocess, and transform raw data into a usable format. Analysts must also be skilled in exploratory data analysis to uncover patterns, correlations, and anomalies within insurance datasets. This skill is crucial for identifying key insights that can inform business decisions and risk assessment.
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Statistical Analysis: Statistical analysis is at the core of insurance data analytics. Analysts must be proficient in statistical methods to assess risk, model claim frequencies and severities, and conduct actuarial analyses. This skill is essential for pricing insurance products accurately and for making underwriting decisions.
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Data Visualization: Data analysts need to translate complex data findings into easily understandable visualizations. Proficiency in data visualization tools like Tableau or Power BI is essential. Clear and compelling visualizations help stakeholders, including underwriters and executives, comprehend data-driven insights and make informed decisions.
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Programming Languages: Data analysts often work with programming languages like Python or R to manipulate and analyze data efficiently. These languages enable analysts to write custom scripts and algorithms for data transformation, statistical modeling, and machine learning applications. Python, in particular, is widely used in the insurance industry for data analytics.
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Machine Learning: Machine learning is increasingly important in insurance data analytics. Analysts must have a foundational understanding of machine learning algorithms and techniques. These skills are used for tasks such as predicting insurance claims, identifying fraud, and optimizing customer segmentation.
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Insurance Domain Knowledge: Understanding the insurance industry's nuances, including various insurance products (e.g., life, health, property, casualty), policy structures, and regulatory requirements, is critical. Domain knowledge allows data analysts to contextualize data and tailor their analyses to address specific insurance-related challenges.
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Business Acumen: Data analysts should have a strong sense of the insurance business. They need to align their data analytics efforts with the company's strategic goals and objectives. This entails understanding the insurance market, competitive landscape, and customer needs.
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Ethical Data Handling: Data privacy and ethical considerations are paramount when working with sensitive customer data in the insurance industry. Analysts must ensure compliance with data protection regulations and industry standards to maintain customer trust and legal integrity.
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Team Collaboration: Effective communication and collaboration skills are essential. Data analysts often work in cross-functional teams alongside underwriters, actuaries, and IT professionals. The ability to communicate data findings clearly and collaborate on solutions is crucial for success.
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Adaptability: The insurance industry, like many others, is continuously evolving. Data analysts should be adaptable and open to learning new data tools, technologies, and methodologies. Staying updated with industry trends and emerging data analytics techniques is important.
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HIRING DATA SCIENTISTS?Â
A data scientist's role in the insurance industry is multifaceted and essential for leveraging data to make informed decisions, optimize processes, and drive business growth.
To hire and retain the best Data Scientists, organisations should:
- Provide competitive salary and benefits packages
- Professional Growth Opportunities
- Innovative Work Environment
- Build a strong employer brand
- Establish strategic partnerships with universities and research institutions.
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UK Hiring Market:
In the competitive landscape of the UK insurance industry, the demand for skilled data scientists is steadily increasing. The UK's insurance sector is renowned for its innovative approach and reliance on data analytics to refine risk assessment and customer engagement. To attract top data science talent, insurance companies in the UK should implement strategic recruitment practices and emphasize their commitment to technological advancements and data-driven decision-making.
US Hiring Market:
In the United States, there is a surging demand for data scientists in the insurance sector. Insurance companies, insurtech firms, and startups are heavily investing in data analytics to optimize underwriting processes, enhance customer experiences, and develop predictive models for risk management. To compete for data science talent in the US, insurance organizations must offer attractive compensation packages and highlight their involvement in cutting-edge data projects.
EU Hiring Market:
The European insurance market exhibits varying levels of demand for data scientists across different countries. Nations with a strong insurance presence, such as Germany, France, and Sweden, are experiencing a substantial need for data scientists proficient in insurance data analytics and regulatory compliance. Insurance companies in these regions should target local talent pools and emphasize their industry expertise to attract skilled data scientists.
Speak to one of our insurance data recruitment experts today to find a data scientist to suit all your needs!
HIRING RISK ANALYSTS?
HIRING DATA ENGINEERS?
HIRING CREDIT ANALYSTS?
In the insurance industry, credit analysts play a pivotal role in assessing and managing the financial risks associated with policyholders and potential clients.
To hire and retain the best Credit Analysts, organisations should:
- Provide competitive salary and benefits packages
- Professional Growth Opportunities
- Innovative Work Environment
- Build a strong employer brand
- Establish strategic partnerships with universities and research institutions.
HIRING BUSINESS INTELLIGENCE ANALYSTS?
In the insurance industry, business intelligence (BI) analysts serve as the data maestros, orchestrating the management and utilization of vast datasets essential for informed decision-making. Their role is multifaceted, encompassing various critical responsibilities that collectively enhance the overall efficiency and effectiveness of insurance operations.
To hire and retain the best BI Analysts, organisations should:
- Provide competitive salary and benefits packages
- Professional Growth Opportunities
- Innovative Work Environment
- Build a strong employer brand
- Establish strategic partnerships with universities and research institutions.
UK Hiring Market:
In the competitive landscape of the UK insurance industry, the demand for skilled BI analysts is on the rise. The UK's insurance sector relies heavily on data-driven insights for risk assessment, customer segmentation, and operational optimization. To attract top BI analyst talent, insurance companies in the UK should implement strategic recruitment practices and emphasize their commitment to leveraging data for competitive advantage.
US Hiring Market:
In the United States, there is a growing demand for BI analysts in the insurance sector. Insurance companies, including carriers and brokers, are increasingly adopting BI solutions to gain insights into customer behaviour, claims processing efficiency, and market trends. To compete for BI analyst talent in the US, insurance organizations should offer attractive compensation packages and showcase their involvement in cutting-edge BI projects.
EU Hiring Market:
The European insurance market also presents opportunities for BI analysts, particularly in countries with strong insurance industry presence such as Germany, France, and Sweden. These regions require BI analysts proficient in data analytics and visualization to support data-driven decision-making and enhance operational efficiency. Insurance companies in these areas should focus on local talent pools and emphasize their industry expertise to attract BI analysts who can unlock valuable insights from data to drive business growth and competitiveness.
Need help to hire the right BI Analyst? Contact us today and choose from our diverse talent pool.
JOBS
LATEST Insurance Data
JOBS
Senior Data Scientist
London
£60000 - £75000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
Senior Data Scientist
£60,000 – £75,000
London or Leicester (1 day a week in office)
This is an opportunity to join a highly regarded data science function where innovation sits at the centre of decision making. Working within a specialist pricing team, you will have the freedom to explore new data sources, develop cutting-edge machine learning models, and shape how customer risk is assessed across a large-scale digital business. If you enjoy solving complex problems and building impactful models from messy, high-volume datasets, this role offers both technical challenge and visibility.
THE COMPANY
They are a market-leading digital organisation with a strong reputation for using data and analytics to drive business performance. Having invested heavily in their data science capabilities, they continue to expand a high-performing analytics community that values curiosity, experimentation, and collaboration.
THE ROLE
As a Senior Data Scientist you will join a specialist team focused on developing innovative approaches to customer risk assessment and pricing.
Specifically, you can expect to be involved in the following:
- Building and deploying predictive machine learning models that improve pricing and customer selection strategies
- Exploring and evaluating new data sources to identify commercial opportunities
- Developing geospatial and footprint models using alternative datasets
- Creating residual and claims-related models to improve business performance
- Working with large, complex, and often unstructured datasets
- Taking ownership of projects from problem definition through to delivery
- Mentoring and supporting junior team members
SKILLS AND EXPERIENCE
The successful Senior Data Scientist will have the following skills and experience:
- Strong commercial experience delivering machine learning and predictive modelling projects
- Advanced Python and SQL skills
- Experience working with large and complex datasets
- Knowledge of machine learning techniques such as XGBoost, CatBoost, or related models
- Experience working in cloud-based environments, ideally Azure
- Strong stakeholder management and communication skills
- Ability to translate business challenges into analytical solutions
- Experience within insurance is valuable but not essential
BENEFITS
The successful Senior Data Scientist will receive the following benefits:
- Salary between £60,000 – £75,000 – depending on experience
- £5000 annual car allowance
- Performance bonus scheme with on-target bonus and enhanced earning potential
- 10% matched pension contribution
- 27 days annual leave plus bank holidays
- Private medical insurance
- And other benefits
HOW TO APPLY
Please register your interest by sending your resume to Majid Latif via the Apply link on this page.
To Apply for this Job Click Here
Senior Data Scientist
Bexhill-On-Sea
£60000 - £75000
+ Data Science & AI
PermanentBexhill-On-Sea, East Sussex
To Apply for this Job Click Here
Senior Data Scientist
£60,000 – £75,000
London, Leicester or Bexhill (1 day a week in office)
This is an opportunity to join a highly regarded data science function where innovation sits at the centre of decision making. Working within a specialist pricing team, you will have the freedom to explore new data sources, develop cutting-edge machine learning models, and shape how customer risk is assessed across a large-scale digital business. If you enjoy solving complex problems and building impactful models from messy, high-volume datasets, this role offers both technical challenge and visibility.
THE COMPANY
They are a market-leading digital organisation with a strong reputation for using data and analytics to drive business performance. Having invested heavily in their data science capabilities, they continue to expand a high-performing analytics community that values curiosity, experimentation, and collaboration.
THE ROLE
As a Senior Data Scientist you will join a specialist team focused on developing innovative approaches to customer risk assessment and pricing.
Specifically, you can expect to be involved in the following:
- Building and deploying predictive machine learning models that improve pricing and customer selection strategies
- Exploring and evaluating new data sources to identify commercial opportunities
- Developing geospatial and footprint models using alternative datasets
- Creating residual and claims-related models to improve business performance
- Working with large, complex, and often unstructured datasets
- Taking ownership of projects from problem definition through to delivery
- Mentoring and supporting junior team members
SKILLS AND EXPERIENCE
The successful Senior Data Scientist will have the following skills and experience:
- Strong commercial experience delivering machine learning and predictive modelling projects
- Advanced Python and SQL skills
- Experience working with large and complex datasets
- Knowledge of machine learning techniques such as XGBoost, CatBoost, or related models
- Experience working in cloud-based environments, ideally Azure
- Strong stakeholder management and communication skills
- Ability to translate business challenges into analytical solutions
- Experience within insurance is valuable but not essential
BENEFITS
The successful Senior Data Scientist will receive the following benefits:
- Salary between £60,000 – £75,000 – depending on experience
- £5000 annual car allowance
- Performance bonus scheme with on-target bonus and enhanced earning potential
- 10% matched pension contribution
- 27 days annual leave plus bank holidays
- Private medical insurance
- And other benefits
HOW TO APPLY
Please register your interest by sending your resume to Majid Latif via the Apply link on this page.
To Apply for this Job Click Here
Senior AI Product Owner
London
£80000 - £85000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
Senior AI Product Owner
London (Hybrid)
The Company
They are a well-established organisation investing heavily in AI, automation, and innovation. With a growing AI function, they are focused on embedding AI solutions that improve decision-making, operational efficiency, and customer outcomes. This role offers high visibility, autonomy, and the opportunity to influence strategic initiatives.
The Role
* Partner with senior stakeholders to identify, shape, and prioritise AI opportunities across a commercial business area
* Lead discovery workshops to define user needs, business problems, and success metrics
* Manage a portfolio of AI initiatives, balancing business value, feasibility, and risk
* Work with specialist delivery teams to take solutions from concept through to implementation and adoption
* Drive user engagement, training, and change management to maximise value realisation
* Ensure AI solutions align with governance, security, privacy, and responsible AI standards
Your Skills & Experience
* Strong commercial experience in Product Ownership, Product Management, Business Analysis, or Transformation
* Strong understanding of AI and Generative AI technologies and their commercial applications
* Experience delivering digital, data, automation, or AI initiatives with measurable business impact
* Ability to influence senior stakeholders and manage competing priorities
* Excellent workshop facilitation, communication, and stakeholder management skills
* Analytical mindset with the ability to evaluate business value and drive data-led decisions
What They Offer
* Hybrid working model
* Exposure to high-profile AI transformation programmes
* Opportunity to influence enterprise-wide AI strategy
* Clear career progression within a growing AI function
To Apply for this Job Click Here
Senior Data Scientist
Leicester
£65000 - £75000
+ Data Science & AI
PermanentLeicester, Leicestershire
To Apply for this Job Click Here
Senior Data Scientist
Leicester (Hybrid – 1 Day Per Week)
£60,000-£75,000 + £5,000 Car Allowance + 10% Bonus + Outstanding Benefits
THE COMPANY
We’re exclusively partnering with one of the UK’s leading digital insurance businesses to hire two Senior Data Scientists into its highly regarded Alternative Pricing Product (APP) team.
With over four million customers and significant investment in Data Science, Machine Learning and digital transformation, the business has built one of the strongest pricing and analytics capabilities in UK insurance. This is a genuinely innovative environment where Data Scientists are encouraged to challenge conventional pricing methods, explore new data sources and develop cutting-edge machine learning solutions that directly influence commercial decisions.
THE ROLE
Joining a specialist team of six Data Scientists and Analysts, you’ll play a key role in developing the next generation of pricing models across car and van insurance.
Rather than maintaining existing models, you’ll be encouraged to challenge traditional pricing approaches by exploring new datasets and applying innovative machine learning techniques to solve complex commercial problems.
Responsibilities include:
- Building predictive machine learning models using large, complex datasets
- Developing innovative pricing and customer selection models
- Creating footprint (geospatial) models using alternative data sources
- Developing residual models to improve claims prediction accuracy
- Exploring novel datasets to improve pricing performance
- Taking existing V1 models and evolving them into production-ready V2 solutions
- Working closely with Pricing, Data Science and Engineering teams
- Mentoring a Graduate Data Scientist while leading your own projects from concept through to delivery
YOUR SKILLS AND EXPERIENCE
- Strong Python and SQL experience
- Commercial Machine Learning experience
- Strong predictive modelling background
- Comfortable working with large, messy datasets
- Experience solving complex business problems using data
- Experience mentoring or supporting junior team members
- Exposure to model deployment is beneficial but not essential
- Experience within Insurance, Financial Services, Gaming or another digital-first business is advantageous
Experience with Azure Machine Learning, Graph-based models or geospatial modelling would be beneficial but is not essential.
THE BENEFITS
- Salary up to £75,000 (up to £80,000 for exceptional candidates)
- £5,000 annual car allowance
- 10% target bonus (up to 20%)
- Hybrid working (1 day per week in the office)
- Choice of London or Leicester or Bexhill office, with monthly London travel fully expensed
- Private Medical Insurance
- 10% matched pension
- 27 days annual leave plus bank holidays
- Buy or sell up to 5 days annual leave
- Life Assurance and Income Protection
- Health & Wellbeing package
- Optional dental cover
- Discounts on company products
INTERVIEW PROCESS
- 30-minute introductory conversation with the Hiring Manager
- Take-home case study followed by a 20-minute presentation and technical discussion
- Final leadership and team-fit interview
HOW TO APPLY
Please register your interest by sending your CV to Max Beadle at Harnham via the Apply link on this page.
To Apply for this Job Click Here
AI Engineer
London
£80000 - £85000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
AI Engineer
London (Hybrid – 3x a week)
The Company
They are a large, data-driven organisation investing heavily in artificial intelligence and advanced analytics. Their AI team is focused on building innovative solutions that improve business operations, enhance customer experiences, and drive measurable commercial value. With access to large and complex datasets, they offer an environment where experimentation, collaboration, and technical excellence are encouraged.
The Role
- Design, build and deploy scalable AI and machine learning solutions, taking projects from concept through to production.
- Develop AI-powered applications using Generative AI, Large Language Models and orchestration frameworks.
- Write high-quality Python code and contribute to cloud-native applications and services.
- Apply MLOps best practices, including CI/CD, containerisation, monitoring and observability.
- Partner with data scientists, engineers and business stakeholders to translate business challenges into impactful AI solutions.
- Monitor, evaluate and improve deployed models while ensuring responsible, secure and reliable AI deployment.
Your Skills & Experience
- Strong commercial experience in AI engineering, machine learning engineering or software engineering with applied AI.
- Proven experience building and deploying Generative AI applications using LLMs and orchestration frameworks.
- Strong Python programming skills and understanding of modern backend architectures.
- Experience working with cloud platforms and production-grade AI systems.
- Knowledge of MLOps, CI/CD, containerisation and model monitoring.
- Experience building data pipelines for model training, fine-tuning and inference.
- Solid grounding in machine learning, statistics and model evaluation techniques.
- Strong communication skills with the ability to engage technical and non-technical stakeholders.
- Commitment to responsible and ethical AI development.
What They Offer
- Competitive salary and comprehensive benefits package.
- Hybrid working model.
- Exposure to large-scale AI and machine learning projects.
- Opportunity to shape the direction of a growing AI capability.
- Ongoing professional development and clear career progression.
- Collaborative environment working alongside experienced AI, data and engineering professionals.
How to Apply
If you’re an AI Engineer looking to build and deploy innovative AI solutions in a high-impact environment, please apply today to learn more about this opportunity.
To Apply for this Job Click Here
Pricing Lead
£80000 - £90000
+ Risk Analytics
PermanentEngland
To Apply for this Job Click Here
Pricing Lead
Remote based within UK
£80,000 to £90,000
This is an excellent opportunity for a Pricing Lead to join a growing insurance business where pricing plays a central role in commercial decision-making. You’ll work in a highly visible position with the freedom to shape processes, influence strategy, and take ownership of key pricing capability across the organisation.
The Company
They are a specialist insurer operating within the UK personal lines market. With a modern, technology-driven approach and a strong focus on analytics, they have continued to grow while maintaining a lean and highly capable team. The business values innovation, autonomy, and collaboration, giving employees direct exposure to senior decision-makers and strategic initiatives.
The Role
- Own and develop pricing models, methodologies, and rating approaches across the portfolio.
- Lead enhancements to pricing processes and pricing infrastructure.
- Use Python to develop, refine, and monitor pricing models.
- Support rating engine development and deployment.
- Deliver analytics across pricing performance, underwriting, and portfolio management.
- Develop fraud analytics capabilities and integrate insights into pricing decisions.
- Partner with senior stakeholders to translate technical findings into commercial recommendations.
- Collaborate with teams across underwriting, technology, and the wider business.
- Help shape the future direction of pricing capability as the organisation continues to grow.
Your Skills & Experience
- Strong commercial experience in personal lines pricing, ideally motor insurance.
- Proven pricing modelling experience and understanding of rating methodologies.
- Strong Python skills for analytics and model development.
- Knowledge of pricing governance and the UK insurance market.
- Ability to work independently, influence stakeholders, and communicate technical findings clearly.
- Experience with fraud analytics or rating engine deployment is advantageous.
What They Offer
- Salary of £80,000 to £90,000.
- Annual bonus scheme.
- Flexible hybrid working with occasional meet-ups in London.
- Exposure to senior leadership and strategic business decisions.
- Broad remit spanning pricing, analytics, and fraud.
- Opportunity to shape a growing function and develop your career in a high-impact environment.
- Private medical insurance, life assurance, and generous holiday allowance.
To Apply for this Job Click Here
Junior Software Engineer
London
£30000 - £40000
+ Data Engineering
PermanentLondon
To Apply for this Job Click Here
Junior Software Engineer
up to £40,000
4 days in London
This is a fantastic opportunity to join a high-growth InsurTech where you’ll take ownership of building customer-facing products from day one across multiple insurance lines.
THE COMPANY:
This B-Corp certified InsureTech business places sustainability, fairness, and customer experience at the heart of everything they build, and are now looking for their next Junior Software Engineer.
THE ROLE:
You will take ownership of building and shipping customer-facing products.
Key responsibilities include:
- Building and launching production features
- Contributing to new product launches, partner integrations, and platform improvements
- Owning work end-to-end with a high level of autonomy from day one
- Collaborating closely with Product, Commercial, and Data teams
- Influencing technical decisions and helping shape engineering direction
This is a highly collaborative, high-impact environment with strong expectations and fast progression.
YOUR SKILLS AND EXPERIENCE:
You will bring strong capability in:
- Excellent problem–solving ability and engineering fundamentals
- Strong academic background (with a preference for a STEM degree)
- Experience with JavaScript (Angular), Python, or similar languages
- Ability to work across full-stack environments and learn new technologies quickly
- Clear communication skills and a proactive, ownership-driven mindset
THE BENEFITS:
You will receive a salary up to £40,000 depending on experience, along with a comprehensive benefits package.
HOW TO APPLY:
Please register your interest by sending your CV to Molly Bird via the apply link on this page.
To Apply for this Job Click Here
Customer Experience Optimisation Manager
£50000 - £60000
+ Digital Analytics
PermanentEssex
To Apply for this Job Click Here
Customer Experience Optimisation Manager
Remote (UK) | 2 Days Per Month in Essex (London Zone 6)
Up to £60,000 + 15-20% Discretionary Bonus
Intro
An exciting opportunity to join one of the UK’s leading travel insurance groups as they continue their international expansion. This role offers full ownership of the end-to-end customer journey, leading CRO strategy, experimentation and digital optimisation across multiple consumer brands.
THE COMPANY
Our client is an award-winning travel insurance group that has helped over 30 million customers since launching in 2000. With operations across the UK and Australia, and further international expansion planned, they are recognised as one of the Top 10 Insurance Companies to Work For in the UK. Their business is built around innovation, experimentation and delivering exceptional digital customer experiences.
THE ROLE
You’ll own the end-to-end digital customer journey, developing and delivering a strategic CRO roadmap that improves conversion, retention and overall customer experience.
Working across Marketing, UX, Engineering, Pricing and Customer Operations, you’ll lead experimentation programmes, use data to identify optimisation opportunities, present recommendations to senior stakeholders and ensure successful ideas are implemented across the business.
This is a strategic, hands-on role with significant autonomy and visibility.
YOUR SKILLS AND EXPERIENCE
- Strong experience in Conversion Rate Optimisation (CRO) and experimentation.
- Hands-on A/B testing experience using platforms such as AB Tasty, Optimizely, VWO or similar.
- Experience with analytics platforms including Google Analytics or equivalent.
- Strong understanding of tagging, front-end implementation, experimentation architecture and UX/UI principles.
- Proven ability to own optimisation projects from strategy through to delivery.
- Excellent stakeholder management and presentation skills.
- Experience in agency or in-house environments considered.
- Permanent employment background preferred (no freelance-only experience).
THE BENEFITS
- Up to £60,000 salary.
- 15-20% discretionary bonus.
- Remote-first working with just two office days per month.
- Join a collaborative and social team.
- Opportunity to shape optimisation strategy across multiple consumer brands.
- International business with ambitious growth plans.
- Three-stage interview process completed entirely online.
HOW TO APPLY
Please register your interest by sending your CV to Max at Harnham via the Apply link on this page.
To Apply for this Job Click Here
Dataops Manager
City of London
£65000 - £75000
+ Data Engineering
PermanentCity of London, London
To Apply for this Job Click Here
Data Operations Manager
up to £75,000 + Benefits
London (Hybrid)
This is a fantastic opportunity to join one of the UK’s most innovative insurance brands, where you can take ownership of Data Operations across a large-scale, business-critical data environment supporting analytics, machine learning, engineering and architecture teams.
THE COMPANY:
This insurance company is continuing to invest heavily in its data platforms, cloud technologies and data-driven customer experience and are now looking for a Data Operations Manager to take ownership and ensure the organisation’s data platforms remain reliable, scalable and compliant.
THE ROLE:
This role is highly stakeholder-facing and focuses on operational leadership rather than hands-on engineering. You’ll oversee third-party suppliers and offshore teams, manage incidents and service performance, drive governance initiatives and ensure data products are delivered effectively across the business.
Key responsibilities include:
- Leading Data Operations across a complex cloud and data ecosystem
- Managing suppliers, offshore teams and support resources
- Driving incident management, service improvements and SLA performance
- Ensuring environments remain scalable, compliant and fit for purpose
- Overseeing data pipeline reliability and operational performance
- Supporting deployment, release and change management processes
- Providing regular operational reporting and KPI tracking to senior stakeholders
- Working closely with Data Engineering, Machine Learning and Architecture teams to ensure seamless data delivery
- Maintaining governance, audit and regulatory compliance standards
- Supporting the migration and evolution of large-scale data platforms across GCP and AWS environments
YOUR SKILLS AND EXPERIENCE:
You will bring strong capability in:
- Data Operations, Data Engineering Operations or Data Platform Management
- Leading technical teams, suppliers and offshore resources
- Incident management, service delivery and operational governance
- Stakeholder management across both business and technology functions
- Delivering technology and data change programmes within complex organisations
- Managing data environments, deployments and release processes
- Building operational frameworks, reporting packs and performance metrics
- Working within regulated industries such as Insurance, Financial Services, Healthcare or similar
- Experience with GCP and large-scale SQL Server environments
- Exposure to Spark, Kafka, SSIS and Power BI
- Experience supporting Machine Learning environments and data products
THE BENEFITS:
You will receive a competitive salary up to £75,000 depending on experience, alongside an outstanding benefits package.
HOW TO APPLY:
Please register your interest by sending your CV to Molly Bird via the apply link on this page.
To Apply for this Job Click Here
Data Analyst – FTC
London
£50000 - £55000
+ Advanced Analytics & Marketing Insights
PermanentLondon
To Apply for this Job Click Here
Data Analyst (FTC – 6 Months)
London or Oxford (Hybrid 2-3 days) | Up to £55,000
No sponsorship offered – must have full UK working rights
An exciting opportunity has arisen for a Data Analyst to join a highly data-driven organisation on an initial 6-month fixed-term contract. This role offers the chance to support a business-critical regulatory programme, working with large and complex datasets to deliver accurate analysis, reporting, and data extracts. If you thrive in a SQL-focused environment and enjoy working on high-impact projects where precision matters, this could be an excellent fit.
The Company
They are an established, technology-led financial services organisation with a strong emphasis on data and analytics. Operating within a regulated environment, they use data to support critical business decisions, customer outcomes, and compliance requirements.
Their analytics function works across the organisation, partnering with teams to provide insights, reporting, and operational support. Data plays a central role in their decision-making, creating an environment where analytical expertise is highly valued.
The Role
As a Data Analyst, you will join a collaborative analytics team supporting a major regulatory programme. This is a hands-on position focused on extracting, manipulating, and analysing data to support reporting, operational processes, and stakeholder requirements.
Key responsibilities include:
- Supporting a large-scale regulatory and customer remediation programme
- Writing, maintaining, and optimising SQL queries for data extraction and analysis
- Processing and fulfilling high volumes of data requests
- Producing accurate data extracts, reports, and management information
- Working with large and complex datasets to identify relevant information
- Ensuring data quality, accuracy, and auditability in all outputs
- Collaborating with stakeholders across analytics and wider business functions
- Supporting reporting requirements within a regulated environment
Your Skills & Experience
You will have:
- Strong commercial SQL experience with advanced data manipulation and querying skills
- Experience working with large datasets and complex extraction requests
- Excellent attention to detail and a highly accurate approach to analytical work
- Experience delivering reporting and data outputs to business stakeholders
- The ability to work effectively within a fast-paced, delivery-focused environment
- Availability to start within a reasonable timeframe
Desirable experience:
- Financial services experience
- Exposure to regulated or compliance-driven environments
- Experience working with complaints, regulatory, or customer remediation datasets
- Tableau or other dashboarding and visualisation tools
What They Offer
- Salary up to £55,000
- 6-month fixed-term contract
- Hybrid working with offices in London and Oxford
- Attendance in the office 2-3 days per week
- Flexibility to be based from either location
- Travel expenses covered when travelling between offices for business requirements
- Opportunity to work on a high-profile regulatory programme with significant business impact
- Exposure to senior stakeholders and a highly regarded analytics function
How to Apply
If you’re a SQL-focused Data Analyst looking for a high-impact opportunity within a data-driven organisation, please apply with your CV to learn more about the role and company.
To Apply for this Job Click Here
Senior Data Scientist
Leicester
£60000 - £75000
+ Data Science & AI
PermanentLeicester, Leicestershire
To Apply for this Job Click Here
Senior Data Scientist
£60,000 – £75,000
London or Leicester (1 day a week in office)
This is an opportunity to join a highly regarded data science function where innovation sits at the centre of decision making. Working within a specialist pricing team, you will have the freedom to explore new data sources, develop cutting-edge machine learning models, and shape how customer risk is assessed across a large-scale digital business. If you enjoy solving complex problems and building impactful models from messy, high-volume datasets, this role offers both technical challenge and visibility.
THE COMPANY
They are a market-leading digital organisation with a strong reputation for using data and analytics to drive business performance. Having invested heavily in their data science capabilities, they continue to expand a high-performing analytics community that values curiosity, experimentation, and collaboration.
THE ROLE
As a Senior Data Scientist you will join a specialist team focused on developing innovative approaches to customer risk assessment and pricing.
Specifically, you can expect to be involved in the following:
- Building and deploying predictive machine learning models that improve pricing and customer selection strategies
- Exploring and evaluating new data sources to identify commercial opportunities
- Developing geospatial and footprint models using alternative datasets
- Creating residual and claims-related models to improve business performance
- Working with large, complex, and often unstructured datasets
- Taking ownership of projects from problem definition through to delivery
- Mentoring and supporting junior team members
SKILLS AND EXPERIENCE
The successful Senior Data Scientist will have the following skills and experience:
- Strong commercial experience delivering machine learning and predictive modelling projects
- Advanced Python and SQL skills
- Experience working with large and complex datasets
- Knowledge of machine learning techniques such as XGBoost, CatBoost, or related models
- Experience working in cloud-based environments, ideally Azure
- Strong stakeholder management and communication skills
- Ability to translate business challenges into analytical solutions
- Experience within insurance is valuable but not essential
BENEFITS
The successful Senior Data Scientist will receive the following benefits:
- Salary between £60,000 – £75,000 – depending on experience
- £5000 annual car allowance
- Performance bonus scheme with on-target bonus and enhanced earning potential
- 10% matched pension contribution
- 27 days annual leave plus bank holidays
- Private medical insurance
- And other benefits
HOW TO APPLY
Please register your interest by sending your resume to Majid Latif via the Apply link on this page.
To Apply for this Job Click Here
Senior Data Scientist
City of London
£70000 - £75000
+ Data Science & AI
PermanentCity of London, London
To Apply for this Job Click Here
Senior Data Scientist, Pricing
London| Competitive Salary up to £75,000 + Bonus + Car Allowance
This is an opportunity to join a highly data-driven organisation where pricing, analytics, and machine learning sit at the heart of business strategy. You will work on innovative data science initiatives that directly influence risk assessment, pricing decisions, and commercial performance, while helping to shape the next generation of predictive modelling capabilities.
The Company
They are a well-established consumer-focused organisation undergoing significant investment in data, analytics, and technology. With a strong emphasis on innovation, they use advanced machine learning and predictive modelling to support strategic decision-making and deliver better customer outcomes.
Their analytics community brings together Data Scientists, Analysts, and Data Engineers who collaborate to solve complex business challenges. They foster a culture of curiosity, continuous improvement, and knowledge sharing, creating an environment where new ideas are encouraged and valued.
The Role
You will play a key role in building and deploying advanced machine learning solutions that support pricing and risk decision-making.
Responsibilities include:
- Developing predictive models focused on risk, claims outcomes, fraud detection, and other key business metrics.
- Creating and maintaining analytical tools that improve portfolio management and commercial performance.
- Identifying, evaluating, and extracting value from new internal and external data sources.
- Engineering new features and rating factors to enhance existing pricing algorithms.
- Managing the full machine learning lifecycle, from exploratory analysis through to deployment, monitoring, and model refresh activities.
- Working closely with Data Scientists, Data Engineers, Analysts, and business stakeholders to translate challenges into impactful solutions.
- Exploring emerging machine learning techniques and assessing their commercial application.
Your Skills & Experience
- Strong commercial experience delivering machine learning projects from initial exploration through to deployment and ongoing optimisation.
- Advanced Python and SQL skills.
- Experience with Azure Machine Learning, Azure cloud technologies, and Git.
- Proven ability to communicate technical concepts to a range of stakeholders and influence decision-making.
- Experience working across multidisciplinary data and analytics teams.
- Strong problem-solving capabilities and a track record of delivering high-quality analytical solutions.
- An interest in applying innovative data science techniques to real-world business challenges.
What They Offer
- Competitive salary package.
- Annual performance bonus.
- Car allowance.
- Hybrid and flexible working arrangements.
- Private medical insurance.
- Generous pension contributions and life assurance.
- Income protection and a broad range of financial wellbeing benefits.
- Employee assistance and wellbeing support programmes.
- 27 days annual leave plus bank holidays, with additional flexibility options.
- Ongoing training, development, and clear opportunities for career progression within a growing data science function.
How to Apply
If you are a Senior Data Scientist with strong machine learning expertise and a passion for solving commercial problems through advanced analytics, apply today to discuss this opportunity in more detail.
To Apply for this Job Click Here
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FAQ:
What does a Data Analyst do in insurance?Â
- A data analyst in the insurance industry plays a vital role in extracting meaningful insights from vast datasets to inform decision-making, improve operational efficiency, and manage risk effectively.
How much do insurance analysts make in the UK?
- The average salary for an Insurance Analyst in the UK is £33,819 per year. However, Salaries may differ by location, with analysts in London typically earning higher incomes due to the city's higher cost of living.
What are the different types of insurance analysts?
There are several different types of insurance analysts who specialise in various areas.
- Fraud Analysts: These analysts specialise in identifying and preventing fraudulent insurance claims. They do this through the use of data analysis and investigative techniques to detect suspicious activities.
- Claims Analysts: This type of analyst will investigate claims made by policyholders. They verify the validity of the claims and assess the extent.
- Actuarial Analyst: This type uses mathematical and statistical models to assess and predict risk. This helps insurance companies set rates & estimate future liabilities.Â
- Market Research Analysts: These Analysts study industry trends, customer behaviour & their competitors. All so that they can provide insights for their insurance companies. Which use them to identify new market opportunities & marketing strategies.
- Risk Analysts: Asses and manage various types of risks that insurance companies face, this includes financial, operational & market risks. A big part of their responsibilities is developing risk mitigation strategies to safeguard the company's financial stability.Â
What is an insurance analytics platform?
- A risk management software solution, specially designed to help insurance companies leverage data analytics to improve their decision-making, manage risks more effectively and manage risks more efficiently. The data provides analysts with the insights they need to inform key stakeholders of potential threats to and opportunities for the business.
How big is the insurance analytics market?
- As of 2022 & on a global scale, the insurance analytics market was valued at $11.71 Billion. It is expected to grow at a rate of 15.4% from 2023 through 2029. With an eventual value of $31.92 Billion.
How is data analytics transforming the insurance industry?Â
- The main aspect of data analytics that has proven to be game-changing is Cloud Computing. Cloud computing has and continues to improve the performance of analytics in real-time and in greater depth. Â
Why do we need data analytics in the insurance industry?
- With data analytics, an insurer enables itself to optimise every single aspect of its business using insights from data. This is known as data-driven decision-making.Â
Industry Trends
In the world of insurance, stability has traditionally been the cornerstone, allowing for predictable risk assessment and steady growth. However, the once steadfast foundations of this industry are undergoing a profound transformation. Over the past few years, a series of short-term crises have shaken the very core of insurance. From a global pandemic to political unrest, supply chain disruptions, and extreme weather events, the landscape is evolving in ways unimaginable just two decades ago.
These short-term crises are not isolated incidents but rather symptomatic of larger, long-term trends. Previously, we referred to these trends as STEEP factors, encompassing Social, Technological, Economic, Environmental, and Political influences. Today, their impact is more pronounced than ever. Social instability, technological disruption, shifting demographics, and climate change are converging to create a fractured world. Insurers now face a daunting array of intensifying risks, both in terms of variety and frequency.
Consequently, these developments have brought about significant changes within the insurance industry itself. Let's explore some of these transformative shifts:
Market Evolution
The traditional insurance market is undergoing a seismic shift. The rise of digital channels and an expanded network of distribution points, including partnerships and embedded options, is disintermediating markets. This proliferation of policy options and easier access challenges the established dominance of carriers. Barriers to entry are diminishing, setting the stage for increased competition and innovation.
Operational Adaptation
Even before the pandemic, insurers were grappling with substantial changes across their operations. In multiple PwC CEO surveys, insurance leaders consistently identified disruption as their primary challenge. The pandemic further accelerated these changes, pushing the workforce and customer interactions into the virtual realm. This shift stressed various functions, including IT, HR, and sales, while upending many established assumptions and behaviours. The industry responded by experimenting with new approaches, but a sense of caution lingers as insurers remain vigilant for unforeseen challenges.
Technological Revolution
Insurers are striving to become tech-enabled, leveraging data from multiple sources to rapidly assess and price risk. Additionally, they aim to provide seamless customer experiences, offering information and insurance precisely when clients need it. Achieving this vision requires a flexible technological infrastructure and a strategic IT function. While progress is evident, most carriers still have a substantial distance to cover before becoming truly tech-enabled, as opposed to merely 'digital.'
Environmental and Social Responsibility
Environmental, Social, and Governance (ESG) considerations are now central to the insurance industry's continued relevance. Compliance with reporting requirements and maintaining a positive brand image are just the tip of the iceberg. Insurers are extending their responsibilities to help clients and society at large mitigate natural and human catastrophes, cybercrime, and other loss incidents. By doing so, they reduce claims, boost profitability, and ensure their long-term viability as carriers.
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These proactive approaches not only reduce claims but also boost profitability and ensure carrier viability. As insurers grapple with these challenges, we anticipate four likely approaches:
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Incremental Change: This aligns with the current and historical norm for most carriers. They adapt incrementally, often reactively, in response to STEEP developments. This approach involves modernizing certain key operational aspects, such as claims processing and customer service, albeit without a comprehensive vision for how cloud and digital transformation can enhance broader business and operations. Incremental change also includes defending or expanding market share, primarily by competing on price and refining loss mitigation and prevention measures. It often involves short-term cost-cutting and a slow adoption of data-driven service improvements. This approach may lack full funding and consistent C-suite support.
- While it modernizes and enhances certain critical operational facets, such as claims processing, and customer service features like autopay and self-service options, it frequently falls short in adopting a comprehensive enterprise-wide perspective on how cloud and digital transformation can truly elevate the broader spectrum of business and operational functions
- Safeguards its market position and bolsters its brand image among specific customer segments, usually by engaging in price-based competition.
-
Enhances the improvement of loss prevention and mitigation on the periphery.
-
Reduces costs usually by implementing short-term expense reductions.
-
Utilizes data at a leisurely pace when it comes to enhancing service experiences.
-
Employs data at a relaxed rate when improving service encounters.
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The Customer-First Approach: Some insurers are restructuring their business and operating models to place the customer at the forefront. This entails aligning offerings and services with evolving customer needs over time. on the customer's needs. This entails fashioning personalized, all-encompassing insurance packages right at the moment of purchase, while seamlessly eliminating any friction by amalgamating service and support across our array of offerings.
-
The principle that carrier and customer success are indistinguishable is fully endorsed by business and operating models.
-
Encompasses a wide range of consumer and risk data sourced from sensors, telematics, and unstructured data to tailor coverage, offer a smooth service experience, mitigate risks, and earn the confidence of customers.
- Provides user-friendly and educational AI-driven insurance and financial solutions for various stakeholders, including employers and their staff (group), enterprises (both commercial and personal lines), individual clients (across all coverage categories), and agents (across all business sectors).
-
Disseminates data from the mentioned applications and others both within the company and to pertinent collaborators in order to uphold a live grasp of customer requirements, actions, and risk assessments.
-
Aids policyholders and the community in proactively preventing losses by shifting from relying on probability-based risk management to adopting a deterministic approach. This, in turn, leads to a decrease in claim payments and an enhancement in overall profitability.
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Pragmatic Evolution: Insurers adopting this approach orchestrate coverages, services, and support in response to changing customer requirements, offering a flexible and adaptable insurance experience.
-
Enhances the potential of cloud and digital advancements by reinventing the customer journey, establishing a beneficial cycle of support between technological empowerment, dissemination, and customer assistance.
-
Facilitates the process of transformation by optimizing crucial processes and mitigating risks in order to boost income, foster business creativity, encourage expansion, and enhance adaptability.
-
Explorations involving interconnected, multifaceted points of engagement, encompassing ecosystems and incorporated insurance.
-
Tailors insurance policies and offers convenient (self-)service through the utilization of consumer and market information to craft suitable, AI-informed options for specific customer groups.
-
To optimize the efficiency of AI from its inception and throughout its lifecycle, an automated framework is employed to gauge the effectiveness of AI bots.
-
Ensuring customer retention involves simplifying policy renewal procedures and showing careful consideration regarding the mode and frequency of communication.
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Radical Reinvention: A few visionary insurers are creating unique business and operating models that redefine insurance and minimize risk. They aim to revolutionize the industry rather than merely adapt to change.
-
Partnerships play a crucial role in our strategic approach due to the reduced barriers to entry and the expanded array of consumer touchpoints, coverages, and coverage options. This requires us to move away from conventional business and operating models.
-
Consequently, inclusion is effortlessly integrated into virtually any transaction's point of sale through collaborative alliances and interconnected systems.
-
Utilizes cutting-edge artificial intelligence that functions discreetly, preemptively identifying the requirements of customers to the extent that it can adjust insurance policies appropriately with minimal or even no intervention from the purchaser.
-
Utilizes the information within its reach to collaborate closely with policyholders, communities, governmental, and private entities in order to proactively improve the factors contributing to and thwart the occurrence of natural disaster losses and cyberattacks.
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