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
Graduate Business Analyst
Bournemouth
£26000 - £30000
+ Advanced Analytics & Marketing Insights
PermanentBournemouth, Dorset
To Apply for this Job Click Here
Associate Information Analyst
Bournemouth/Hybrid
Up to £28,000
Overview
A strong entry point into a data career, this role offers hands on SQL work alongside real business exposure. You will develop skills in data requirements, quality, and stakeholder engagement while working across a range of projects.
The Company
They are a well-established UK based organisation with a growing data function and strong investment in analytics. The business promotes a collaborative environment where data plays a key role in decision making. You will join a supportive team with clear opportunities to learn and progress.
The Role & Responsibilities
- Gather and interpret data requirements from business stakeholders
- Translate needs into clear data specifications
- Use SQL for data interrogation, testing, and validation
- Support data quality improvement and issue resolution
- Work on both transformation projects and BAU changes
- Collaborate with engineering, analytics teams, and business users
- Build or support basic Power BI or Tableau outputs when needed
Your Skills & Experience
- Strong SQL fundamentals
- Experience using Excel for data analysis
- Exposure to BI tools such as Power BI or Tableau
- Ability to balance technical work with stakeholder communication
- Curious, proactive, and confident asking questions
How to Apply
Apply now to start or grow your career in a business facing data role.
To Apply for this Job Click Here
Graduate Business Analyst
Bournemouth
£28000 - £30000
+ Advanced Analytics & Marketing Insights
PermanentBournemouth, Dorset
To Apply for this Job Click Here
Associate Information Analyst
Bournemouth | Hybrid working (2 days per week on-site) | £28,000 – £30,000. No sponsorship offered now or in the future!
This is not a data analyst position!
This is a great opportunity for someone early in their data or information career who wants exposure beyond dashboards and reporting. You will sit at the intersection of business and data, gaining hands-on experience with requirements gathering, data quality and stakeholder engagement within a supportive analytics environment. If you enjoy understanding how data flows through systems and asking the right questions to solve business problems, this role offers strong foundations and long-term progression.
The Company
They are a well-established UK organisation operating in the health and insurance space, with a strong focus on using data to improve decision-making and customer outcomes. The business has a collaborative, purpose-led culture and a growing analytics community spread across multiple UK locations. Data plays a central role in how teams work, with ongoing investment in platforms, people and transformation initiatives.
The Role
- Act as a bridge between business stakeholders and data or engineering teams.
- Gather, clarify and document data requirements, ensuring business needs are clearly understood.
- Use SQL to interrogate data, support validation, testing and issue resolution.
- Assess the impact of changes to existing data assets and support continuous improvements.
- Contribute to larger data and systems change projects as well as smaller BAU enhancements.
- Support the creation of basic data outputs and occasional dashboards, where required.
- Work closely with analysts, engineers and architects across a range of initiatives.
Your Skills and Experience
- Strong foundational SQL skills for data interrogation and validation.
- An understanding of how data is structured and moves through systems.
- Exposure to BI tools such as Power BI or Tableau.
- Confidence communicating with both technical and non-technical stakeholders.
- A curious, problem-solving mindset with an interest in how data supports the business.
- Comfortable working across requirements, testing and data quality rather than pure reporting.
What They Offer
- Competitive salary between £28,000, with flexibility up to £30,000.
- Discretionary bonus scheme paid biannually.
- Hybrid working model with two days per week in the Bournemouth office.
- Comprehensive benefits package aligned with the wider business.
- Clear development pathway within an established data and information function.
How to Apply
If you are looking to build a career in information and data, with exposure to real business change, please apply via the organisation’s online application process.
To Apply for this Job Click Here
Associate Information Analyst
Bournemouth
£25000 - £280000
+ Advanced Analytics & Marketing Insights
PermanentBournemouth, Dorset
To Apply for this Job Click Here
ASSOCIATE INFORMATION ANALYST
BOURNEMOUTH/HYBRID
UP TO £28,000
This is a standout opportunity for an early career data professional to step into a role that goes beyond dashboards and reporting. You will sit at the intersection of business and data, gaining exposure to end to end data processes while building strong stakeholder and technical skills. If you enjoy asking questions, understanding how data drives decisions, and working on meaningful change, this role offers an excellent foundation for long term progression.
ROLES AND RESPONSIBILITIES:
The Associate Information Analyst will:
- Act as a bridge between business stakeholders and technical teams, translating requirements into clear data needs
- Support requirements gathering through workshops, interviews, and analysis
- Work closely with data engineers to ensure data flows and solutions are correctly implemented
- Write and use SQL to interrogate data, validate outputs, and support testing activities
- Assist with data validation and quality assurance processes
- Contribute to both transformation projects and ongoing improvements
- Support the maintenance and monitoring of data outputs and pipelines
- Help diagnose and resolve data issues while communicating effectively with stakeholders
YOUR SKILLS AND EXPERIENCE:
- Strong foundation in SQL for data analysis and validation
- Understanding of how data is structured and flows through systems
- Exposure to BI tools such as Power BI or Tableau
- Confident using Excel for data interrogation and analysis
- Strong problem solving ability with a curious and analytical mindset
- Comfortable engaging with stakeholders and asking insightful questions
- Interest in working across both technical and business focused tasks
APPLY BELOW
To Apply for this Job Click Here
SAS Model Developer
London
£380 - £400
+ Data Engineering
ContractLondon
To Apply for this Job Click Here
SAS Model Developer (Contract)
London, Outside IR35
This contract offers the chance to own end-to-end model delivery within a lean analytics function, working on business‑critical modelling initiatives with real production impact. You will join a small, highly capable team where autonomy, technical depth, and clear delivery are valued.
The Company
They are a data‑driven organisation with a strong focus on pricing and analytics. Operating within a compact analytics team, they are investing in robust, scalable modelling solutions to support ongoing decision‑making. The environment is collaborative and delivery‑focused, with senior stakeholders closely engaged in the outcomes of the work.
The Role and Deliverables
- Design, develop, and enhance statistical and predictive models using SAS across the full model development lifecycle.
- Build modelling datasets, feature engineering processes, and variable transformations.
- Develop model logic, segmentation rules, scoring code, and scenario analysis.
- Carry out model validation, back‑testing, sensitivity analysis, and performance monitoring.
- Convert prototype models into production‑ready SAS solutions with appropriate documentation.
- Work with analytics, technology, and business stakeholders to deploy and optimise models in controlled environments.
Your Skills & Experience
- Strong experience developing statistical and predictive models in SAS.
- Advanced SAS programming capability including Base SAS, Data Step, SAS SQL, and macro development.
- Proven ownership of models from development and validation through to deployment and optimisation.
- Solid understanding of regression‑based modelling, segmentation, forecasting, and model performance measurement.
- Confidence working independently and communicating complex modelling concepts to non‑technical stakeholders.
How to Apply
Apply now to discuss how your SAS modelling experience could contribute to this high‑impact contract role.
To Apply for this Job Click Here
Customer Selections and Analytics Consultant
Stratford-upon-Avon
£45000 - £50000
+ Advanced Analytics & Marketing Insights
PermanentStratford-upon-Avon, Warwickshire
To Apply for this Job Click Here
Customer Selections & Analytics Consultant
£45,000 to £50,000
Stratford-upon-Avon (1 day per week on-site)
This is an excellent opportunity to join a well-established organisation investing in its customer data and campaign capabilities. You will play a key role in delivering data-driven marketing activity while gaining exposure to modern data platforms, customer analytics, and advanced campaign optimisation.
THE COMPANY
They are a highly regarded UK-based organisation operating across insurance and financial services, with a strong reputation for customer-centricity and long-term value.
THE ROLE
As a Customer Selections & Analytics Consultant you will sit within a specialist Customer Selections and Analytics team, working alongside SQL specialists and analytics professionals to deliver high-quality campaign selections and insights.
Specifically, you can expect to be involved in the following:
- Translating campaign briefs into structured technical requirements.
- Building and executing customer selections using SQL.
- Joining and manipulating large datasets across CRM, transactional and behavioural data.
- Supporting campaign deployment via API integrations with CRM platforms.
- Partnering with analytics teams to support test-and-learn initiatives and performance measurement.
- Planning and delivering selections aligned to campaign timelines and business priorities.
- Communicating insights clearly to stakeholders to support data-driven decisions.
SKILLS AND EXPERIENCE
The successful Customer Selections & Analytics Consultant will have the following skills and experience:
- Strong SQL skills and experience working with complex datasets.
- Background in campaign selections, CRM data or customer analytics.
- Ability to translate business requirements into technical outputs.
- Exposure to data visualisation tools such as Power BI or similar is beneficial.
BENEFITS
The successful Customer Selections & Analytics Consultant will receive the following benefits:
- Salary between £45,000 – £50,000 – depending on experience
- A 17.5% bonus 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
Data Scientist
London
£40000 - £60000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
Data Scientist
London – 2x a week
The Company
They are a rapidly scaling European insurer with a strong track record of growth and significant external investment. Their operating model is highly data driven, with advanced analytics underpinning pricing and underwriting decisions. The business fosters a high performance culture and invests heavily in developing talent, particularly individuals with strong academic foundations and high potential. Their UK presence is a key strategic focus, with continued expansion of their analytics function.
The Role
You will sit within the pricing and underwriting data science team, working on core modelling challenges that directly influence commercial performance. Responsibilities include:
- Developing and improving pricing models to optimise competitiveness in the market
- Identifying and integrating new data sources into modelling approaches
- Building predictive models to simulate customer behaviour and risk outcomes
- Enhancing tariff structures and pricing strategies using advanced analytics
- Collaborating with cross functional teams to drive customer acquisition and growth
- Applying logical reasoning and structured thinking to complex business problems
Your Skills and Experience
- Strong academic background in Mathematics, Physics or a related quantitative discipline
- Proven ability to apply data science or statistical modelling techniques in a commercial or academic setting
- Proficiency in Python or strong capability to learn quickly
- Excellent problem solving skills, with an ability to think logically and communicate reasoning clearly
- Motivated, intellectually curious, and comfortable working in a fast paced environment
- For experienced candidates, commercial exposure to modelling in any industry is welcomed
What They Offer
- Hybrid working with a London base
- Clear progression opportunities in a scaling analytics team
- Exposure to impactful, end to end data science projects
- A high performance environment with strong investment in training and development
How to Apply
Please apply with your CV to be considered for this opportunity.
To Apply for this Job Click Here
Customer Selections Analyst
Nottingham
£45000 - £50000
+ Advanced Analytics & Marketing Insights
PermanentNottingham, Nottinghamshire
To Apply for this Job Click Here
Customer Selections and Analytics Consultant
Hybrid working
Salary up to: £50,000
This is a strong opportunity for a commercially minded analytics professional to combine technical delivery with stakeholder impact. You will play a key role in driving targeted marketing activity and improving campaign performance through data-led insight, working in a highly collaborative environment.
The Company
They are a well-established organisation with a strong customer focus and a growing investment in data and analytics. Analytics plays a key role in shaping marketing effectiveness, customer engagement, and strategic decision making. The business operates in a structured and regulated environment, offering stability alongside the opportunity to influence change through data. They foster a collaborative culture where stakeholder partnerships are central to success.
The Role
- Develop and deliver customer selections for marketing, research, and service communications using SQL
- Ensure campaigns are accurately targeted, compliant, and aligned to business objectives
- Build and enhance dashboards to evaluate campaign performance and test and learn activity
- Provide clear, actionable insight to improve targeting, ROI, and customer engagement
- Work closely with stakeholders to translate business requirements into analytical solutions
- Act as a subject matter expert across customer datasets to support selection and analysis activity
- Communicate complex insights clearly to both technical and non-technical audiences
- Support continuous improvement through feedback loops between selection and performance analysis
- Implement quality assurance processes to ensure outputs are robust and compliant
Your Skills and Experience
- Strong SQL capability for data extraction and customer segmentation
- Experience with data visualisation tools such as Power BI or similar
- Strong commercial experience delivering insight to support marketing or customer strategy
- Ability to manage and influence a range of stakeholders
- Experience presenting data and recommendations clearly, both verbally and in writing
- Comfortable working with complex datasets and translating insight into action
- Understanding of campaign analysis, testing methodologies, and performance measurement
What They Offer
- Structured career progression within a growing analytics function
- Opportunity to influence end-to-end campaign strategy and customer engagement
- Collaborative, supportive team environment with a strong focus on development
How to Apply
If you are interested in using data to drive customer engagement and marketing performance, please apply with your CV to find out more.
To Apply for this Job Click Here
Senior Data Scientist
London
£60000 - £75000
+ Risk Analytics
PermanentLondon
To Apply for this Job Click Here
Senior Data Scientist
Salary
£60,000-£75,000 + bonus
Location + work pattern
London or Leicester | Hybrid working (1 day per week in the office)
THE COMPANY
- A well-established UK general insurance provider with a strong reputation for advanced analytics and data-driven decision making.
- The business operates at scale across multiple personal lines products and continues to invest significantly in modern data platforms and machine learning.
- Data science sits at the core of how the organisation prices risk and drives commercial strategy.
THE ROLE
This is a senior individual contributor role within an innovative pricing function, focused on developing and evolving advanced predictive models. You will work on complex, high-impact modelling problems and help shape the next generation of pricing approaches.
Specifically, you can expect to be involved in:
- Building and enhancing pricing and risk models using large, complex and messy datasets.
- Developing predictive and residual models to better understand expected versus actual outcomes.
- Exploring novel data sources, including geospatial and alternative datasets, to improve customer selection and pricing accuracy.
- Supporting the progression of existing models from early versions into more mature, production-ready solutions.
- Mentoring junior team members and contributing to best practice across the data science community.
YOUR SKILLS AND EXPERIENCE
- Strong experience in predictive modelling using Python and SQL.
- Hands-on experience with modern machine learning techniques such as gradient boosting methods.
- Proven ability to work with large-scale, complex datasets and translate ambiguity into clear analytical approaches.
- Experience deploying models into production environments within a cloud-based platform.
- Ability to communicate technical concepts clearly and support less experienced colleagues.
THE BENEFITS
- Performance-related bonus.
- Car allowance.
- Private medical insurance and health & wellbeing support.
- Generous holiday allowance with the option to buy or sell additional days.
- Pension contribution with employer matching.
- Life assurance, income protection and additional optional benefits.
THE PROCESS
- Initial 30-minute interview focused on experience and approach.
- Technical case study with presentation and discussion.
- Competency-based interview covering leadership and delivery scenarios.
- Final-stage interview focused on team fit and senior stakeholder engagement.
HOW TO APPLY
Please register your interest via the apply link on this page.
To Apply for this Job Click Here
Pricing Analytics Manager
City of London
£60000 - £75000
+ Risk Analytics
PermanentCity of London, London
To Apply for this Job Click Here
Pricing Analytics Manager
Hybrid – 1x day per week (London, Leicester or Bexhill)
£60,000 – £75,000 + car allowance.
This is a high impact pricing analytics role sitting at the centre of portfolio performance and underwriting strategy. You will influence how risk is assessed, priced and managed across a large, complex insurance portfolio, with clear visibility and ownership over commercial outcomes.
The Company
They are a digitally led financial services business with a strong data and analytics capability at the core of decision making. With millions of customers and continued investment in pricing and analytics, they place real emphasis on curiosity, collaboration and constructive challenge. The culture is values driven, focused on delivering fair customer outcomes while achieving sustainable growth.
The Role
You will join a specialist pricing analytics team focused on portfolio oversight and risk performance. Acting as a key link between modelling, pricing and underwriting, you will turn complex performance data into clear, actionable insight.
- Analyse portfolio risk using loss ratios and performance KPIs across modelled segments
- Identify areas of over and under performance and translate findings into portfolio actions
- Provide data driven insight to pricing and modelling teams to inform rate and model changes
- Lead risk selection initiatives and cross functional projects that deliver commercial value
- Communicate insights clearly to senior and non technical stakeholders
- Support underwriting governance and ensure customer outcomes remain fair and appropriate
Your Skills and Experience
- Strong commercial experience in pricing, underwriting or portfolio analytics within insurance or financial services
- High level of confidence working with numerical and statistical data
- Experience using data manipulation or statistical tools, with appetite to develop advanced capability
- Proven ability to critically evaluate information and challenge assumptions
- Clear and confident communicator, comfortable influencing stakeholders
- Proactive mindset with a track record of driving change through insight
What They Offer
- Competitive salary plus £5k car allowance
- Annual performance related bonus
- Flexible hybrid working approach
- Private medical insurance and comprehensive wellbeing support
- Generous pension contributions and life assurance
- 27 days annual leave plus bank holidays, with buy and sell options
- Ongoing training, development and genuine career progression in pricing and analytics
How to Apply
Apply now to learn more about this opportunity and how you can shape portfolio performance through data driven insight.
To Apply for this Job Click Here
Senior Data Scientist
London
£100000 - £130000
+ Risk Analytics
PermanentLondon
To Apply for this Job Click Here
Senior Data Scientist
London
£100,000 to £130,000
This is an opportunity to step into a highly influential data science role within a business where analytics sits at the heart of commercial decision making. You will work on complex, high-impact pricing problems, have clear ownership of your work, and see your models directly shape business outcomes.
The Company
They are a technology-led organisation operating in the insurance space, known for their strong investment in data, analytics and engineering. The business is well funded, ambitious, and sets high standards for analytical thinking and technical quality. Data scientists are viewed as strategic partners, not service providers, and are encouraged to challenge, innovate and drive measurable impact.
The Role
- Deliver data science within a pricing-focused environment, influencing rates, tariffs and overall market competitiveness
- Design, build and refine predictive models to better understand risk, customer behaviour and price sensitivity
- Identify and integrate new data sources to improve pricing accuracy and decision making
- Use simulation and modelling techniques to estimate outcomes such as claim frequency and customer responses to price changes
- Translate complex analysis into clear, commercially focused recommendations for senior stakeholders
Your Skills & Experience
- A strong academic background and Masters degree in a STEM discipline such as mathematics or physics
- Advanced analytical and problem-solving skills, with the ability to articulate business impact clearly
- Strong experience using Python for data analysis and modelling
- Experience building and applying predictive models in a commercial context
- Comfortable working in a fast-paced environment with a high level of ownership and accountability
What They Offer
- Salary between £100,000 and £130,000 plus a comprehensive benefits package
- Hybrid working with a minimum of one day per week in the London office
- Exposure to high-value, business-critical projects with real visibility and influence
- A strong culture of learning, development and progression for high-performing data scientists
To Apply for this Job Click Here
Senior Data Scientist
London
£75000 - £90000
+ Data Science & AI
ContractLondon
To Apply for this Job Click Here
Senior Data Scientist (12 Month FTC)
London (Hybrid, 2 days per week)
The Company
They are a well established health and insurance technology organisation operating at significant scale, combining traditional insurance products with personalised, data driven services. Data Science is a core strategic capability, with strong executive support and a track record of deploying models and AI applications into live customer and internal workflows. The environment balances innovation with the rigour required in a regulated setting.
The Role
As a Senior Data Scientist focused on AI Engineering, you will take ownership of full lifecycle projects, from problem definition through to deployment and monitoring.
- Lead end to end delivery of AI and LLM based solutions across underwriting and insurance journeys
- Build and deploy agentic workflows, RAG pipelines, and LLM powered applications for internal and customer facing products
- Work across structured and unstructured data, collaborating closely with Machine Learning and GenAI specialists
- Own cloud based deployment, CI/CD, and productionisation of models and services
- Partner with product managers, engineers, and business stakeholders to shape requirements and scope projects
- Communicate progress and outcomes clearly, building trust through delivery and technical leadership
This role sits within a balanced team of traditional ML and GenAI specialists, with exposure to both classic modelling and modern AI use cases.
Your Skills and Experience
- Strong Data Science fundamentals and experience delivering classical machine learning models in production
- Hands on experience with LLMs, agentic workflows, and applied AI solutions
- Proven capability deploying models and AI services end to end, including monitoring and optimisation
- Solid engineering mindset with experience in cloud platforms, CI/CD, APIs, and containerised environments
- Confidence owning projects independently and leading delivery in cross functional teams
- Experience working in regulated, customer facing, or large scale data environments is beneficial
What They Offer
- Pension with up to 6 percent employer matching
- Private health and life insurance
- Hybrid working with a central London office location
- Strong likelihood of contract extension based on project delivery
How to Apply
If you are looking to own impactful AI projects in a mature, well supported Data Science environment, apply now to learn more.
To Apply for this Job Click Here
AI Engineer (FTC)
London
£70000 - £90000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
12 Month FTC Role
Senior Data Scientist (12 Month Fixed Term Contract)
London (Hybrid, 2 days per week in the office)
This is a rare opportunity to step into a senior, end to end role where you will take full ownership of high impact data science and AI projects during a critical period of transition. You will work across a genuinely mixed portfolio of traditional machine learning and modern generative AI, with real responsibility for design, deployment, and stakeholder outcomes.
The Role
You will join a blended Data Science and AI Engineering team, covering a maternity leave where projects are already live and business critical. You will own work end to end, from scoping and solution design through to production deployment and ongoing monitoring.
Key responsibilities include:
- Owning and delivering machine learning and AI projects from problem definition to production.
- Designing models from scratch across both structured and unstructured data use cases.
- Building and deploying LLM based solutions including summarisation and agentic workflows.
- Delivering traditional machine learning models using techniques such as gradient boosting.
- Working closely with product, engineering, and business stakeholders to define requirements and trade offs.
- Deploying models using cloud infrastructure, CI/CD pipelines, and MLOps best practices.
- Taking responsibility for monitoring, performance, and ongoing improvement of live models.
Your Skills and Experience
- Strong commercial data science experience with a solid grounding in classical machine learning.
- Hands on experience deploying and owning models in production environments.
- Good understanding of LLMs and modern AI approaches, or clear capability to apply them in production.
- Experience working with cloud platforms and deployment pipelines, with exposure to CI/CD and MLOps.
- Confident working end to end, from exploratory analysis through to scalable deployment.
- Comfortable operating in regulated or complex environments.
- Strong stakeholder management and communication skills, with the ability to translate business needs into technical solutions.
Please note, this is a 12 month FTC
To Apply for this Job Click Here
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2022 is set to be an interesting year for Risk Analytics. According to research, the risk analytics market is expected to be worth around $54.95bn by 2027 and…
How To Get Started In Risk Analytics | Harnham Recruitment post
Risk Analytics has been an integral part of teams across several industries for years. After the 2008 financial crash, whereby $8 trillion was wiped from the…
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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.
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Enhances the improvement of loss prevention and mitigation on the periphery.
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Reduces costs usually by implementing short-term expense reductions.
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Utilizes data at a leisurely pace when it comes to enhancing service experiences.
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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.
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The principle that carrier and customer success are indistinguishable is fully endorsed by business and operating models.
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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).
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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.
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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.
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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.
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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.
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Explorations involving interconnected, multifaceted points of engagement, encompassing ecosystems and incorporated insurance.
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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.
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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.
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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.
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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.
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Consequently, inclusion is effortlessly integrated into virtually any transaction's point of sale through collaborative alliances and interconnected systems.
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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.
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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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