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
Data Scientist
London
£60000 - £75000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
Data Scientist
London, 60,000 to 70,000 plus benefits, hybrid working, no sponsorship
This role offers the chance to step into a high‑impact data science position within a fast‑moving pricing environment where analytics directly influences commercial outcomes. You will work on complex, real‑world modelling problems with genuine ownership and visibility, rather than supporting work at the edges of the business.
The Company
They are a well‑established European insurance business operating in a highly data‑driven and technology‑led environment. With strong backing and ambitious growth plans in the UK, analytics plays a central role in how they compete and respond to market change. The culture is collaborative, fast paced and focused on building advanced analytical capability in‑house.
The Role
- Work within a pricing and underwriting data science team, building and improving predictive models that influence commercial strategy.
- Develop pricing and risk models that balance competitiveness with profitability.
- Explore, evaluate and integrate new data sources to enhance model performance.
- Use statistical thinking, logic and reasoning to simulate customer behaviour, including risk frequency and price sensitivity.
- Communicate insights clearly and influence decision‑making across technical and non‑technical stakeholders.
- Partner closely with machine learning engineers and other data professionals to deploy robust, scalable solutions.
Your Skills and Experience
- Strong commercial experience in data science or statistical modelling within any industry.
- Advanced Python skills for analysis and modelling.
- A solid grounding in statistical or mathematical concepts and applied problem solving.
- Confidence reasoning through complex problems and explaining your approach clearly.
- Experience working with end‑to‑end modelling problems, from concept through to impact.
- You must already have the right to work in the UK, as sponsorship is not available.
What They Offer
- Salary ranging from 60,000 to 75,000 depending on experience.
- Hybrid working with 1 to 2 days per week in the London office.
- High levels of autonomy and ownership over meaningful projects.
- Exposure to a wide range of analytical challenges in a fast‑growing business.
- Clear opportunities for progression as the UK data function continues to scale.
How to Apply
Apply now to learn more about this data science opportunity within a high‑impact pricing team.
To Apply for this Job Click Here
Data Scientist
London
£45000 - £50000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
Data Scientist
London hybrid (1 to 2 days in the office) | £45,000 to £50,000 + benefits
Must have a masters in Maths or Physics from a Russell Group University
No sponsorship.
This is an opportunity to join a fast-growing insurance business at a pivotal stage of its UK expansion. You will sit in a highly analytical pricing and underwriting team, working on commercially critical models that directly influence pricing strategy, customer behaviour, and market competitiveness. The role offers strong ownership, rapid learning, and clear progression in a business that invests heavily in developing its data talent.
The Company
They are a European insurance provider operating in a highly competitive market, known for using data and technology as a core differentiator. Having achieved significant scale in their home market, they are now expanding rapidly across Europe with strong financial backing and ambitious growth plans. The culture is fast paced, highly data driven, and focused on building advanced analytical capability ahead of the market. They place particular emphasis on developing high-potential individuals and giving them exposure to meaningful, business-critical work.
The Role
- Work within the pricing and underwriting function to improve price accuracy and competitiveness
- Build and develop predictive models to better understand risk, customer behaviour, and pricing sensitivity
- Explore and integrate new data sources to enhance existing pricing and risk models
- Simulate customer behaviour, such as claim likelihood and response to pricing changes
- Translate analytical insights into practical recommendations that support new business growth
- Collaborate closely with other data scientists, machine learning engineers, and stakeholders across the business
Your Skills & Experience
- Strong academic background in a quantitative subject such as Mathematics or Physics
- Excellent logical reasoning and problem-solving ability
- Experience applying data science or modelling techniques in a commercial environment, or strong academic project experience
- Python experience is essential, with openness around other tools and technologies
- Ability to communicate complex ideas clearly and reason through problems out loud
- Motivated, curious, and keen to develop quickly in a demanding analytical environment
What They Offer
- Salary from £45,000 to £50,000 for strong Master’s graduates
- Hybrid working with 1 to 2 days per week in the London office
- Exposure to a wide range of pricing and modelling projects with real commercial impact
- Strong learning culture with support, mentorship, and clear development pathways
- Opportunity to join a growing UK analytics function within a well-funded, high-growth business
How to Apply
If you are interested in this Data Scientist role and want to find out more, please apply!
To Apply for this Job Click Here
Data Scientist
London
£45000 - £50000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
Data Scientist
London, 45,000 to 50,000 plus benefits, hybrid working 1 to 2 days per week, No sponsorship available
This is a standout opportunity for a high‑potential graduate to launch a data science career in a business where analytics directly shapes commercial decisions. You will join a pricing team known for developing early‑career talent, offering real ownership, structured learning and exposure to impactful projects from day one.
The Company
They are a fast‑growing European motor insurance business operating in a highly data‑driven, technology‑led environment. Having successfully scaled across multiple markets, they are now investing heavily in their UK analytical capability. The culture is ambitious, collaborative and focused on hiring bright, curious people with strong problem‑solving ability.
The Role
- Work within a data science function aligned to pricing and underwriting.
- Build and improve predictive models to support pricing competitiveness and risk management.
- Use logical reasoning and statistical thinking to simulate customer behaviour, including risk and price sensitivity.
- Explore and assess new data sources to enhance modelling performance.
- Communicate your approach and reasoning clearly when solving complex problems.
- Collaborate closely with experienced data scientists and machine learning engineers.
Your Skills and Experience
- A Masters degree in Mathematics, Physics or a closely related quantitative subject.
- Strong academic performance with a 2.1 or above.
- Excellent logical, analytical and problem‑solving skills.
- Motivation, curiosity and a clear interest in applied data science.
- Ability to explain your thinking and approach when tackling unfamiliar problems.
- Any exposure to Python or analytical programming is beneficial but not essential for graduates.
- You must already have the right to work in the UK, as sponsorship is not available for this role.
What They Offer
- Salary of 45,000 to 50,000.
- Hybrid working with 1 to 2 days per week in the London office.
- Structured training, mentorship and clear development pathways within data science.
- High levels of responsibility and ownership early in your career.
- The chance to grow within a business that genuinely values data and invests in its people.
How to Apply
Apply now to learn more about this graduate data science opportunity within a high‑performing pricing team.
To Apply for this Job Click Here
Pricing Portfolio Analytics Manager
£60000 - £75000
+ Risk Analytics
PermanentEngland
To Apply for this Job Click Here
Pricing Portfolio 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
Data Engineer
Short Hill
$120000 - $140000
+ Data Engineering
PermanentNew Jersey
To Apply for this Job Click Here
Senior Data Engineer
Location: New Jersey
Remote: Hybrid (2 days on-site per week)
Salary: $120,000 – $140,000 base + 10% target bonus (flexible for outstanding profiles)
Visa: No sponsorship
Company
The organization is modernizing a fragmented legacy environment into a cloud-native data platform built on Databricks and Azure. With strong revenue growth and national expansion underway, data engineering has become a strategic pillar to support pricing, risk, analytics, and operational decision-making across the business.
The Role
- Design, build, and optimize end-to-end data pipelines on Databricks using Python, PySpark, and SQL.
- Implement and evolve Medallion architecture standards (Bronze, Silver, Gold) across multiple data domains.
- Develop ingestion frameworks for batch and streaming data, including structured and semi-structured sources.
- Partner with actuarial, analytics, underwriting, claims, and marketing teams to deliver trusted, production-grade data.
- Contribute to data governance, observability, cost optimization, and CI/CD best practices within Databricks.
Desired Profile
- 5-7+ years of experience in Data Engineering with strong, hands-on Databricks expertise.
- Proven ability to build, explain, and own production-grade pipelines from ingestion to consumption.
- Deep understanding of Medallion architecture and schema evolution strategies.
- Strong Python and PySpark coding skills, with solid SQL performance tuning experience.
- Experience working with cloud data lakes (Azure preferred) and modern file formats (Delta, Parquet, JSON, XML).
To Apply for this Job Click Here
Senior Data Scientist
England
£60000 - £75000
+ Data Science & AI
PermanentEngland
To Apply for this Job Click Here
Senior Data Scientist
London or Leicester, hybrid working, £60,000 to £75,000 plus bonus
If you enjoy solving complex, open ended problems and want your models to directly influence real world decisions, this role stands out. You will work in a highly analytical environment where data science is central to pricing strategy, with the freedom to experiment, challenge assumptions, and build genuinely innovative solutions.
The Company
They are a large, digitally focused organisation operating in a consumer market rich with data and complexity. Analytics and data science sit at the heart of how the business assesses risk, prices products, and drives sustainable growth. Significant ongoing investment in technology and cloud infrastructure means data teams are well supported to innovate and deliver impact at scale.
The Role
- Build and improve predictive models that shape pricing and customer selection strategies.
- Work with large, messy datasets to uncover insight and improve commercial outcomes.
- Develop and iterate on advanced machine learning models, including gradient boosting approaches.
- Explore alternative and novel data sources, including geospatial style data, to enhance pricing accuracy.
- Take ownership of models from early exploration through to deployment and iteration.
- Collaborate closely with stakeholders across pricing, analytics, and engineering.
- Support and mentor junior colleagues, contributing to a strong team culture.
Your Skills & Experience
- Strong commercial experience in data science or applied machine learning.
- Demonstrable experience building predictive models used in pricing, risk, or customer decisioning.
- Confidence working end to end across the modelling lifecycle, from problem definition to deployment.
- Strong Python and SQL skills, with experience working in cloud based environments.
- Ability to communicate modelling approaches and results clearly to non technical stakeholders.
- A curious mindset with an interest in improving pricing accuracy through data and innovation.
What They Offer
- Salary between £60,000 and £75,000.
- Additional cash bonus on top of base salary.
- Hybrid working with one day per week in the office.
- Exposure to highly visible, business critical modelling work.
- Strong progression and development opportunities within an established data science function.
How to Apply
Apply now to explore how this Senior Data Scientist role could be the next step in your career.
To Apply for this Job Click Here
Senior Data Scientist
London
£60000 - £75000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
Senior Data Scientist
London, hybrid, one day a week on site.
£60,000 to £75,000 plus £5,000 cash allowance
This is an exciting opportunity to join a high‑performing data science function that is known in the market for its innovation, scale, and technical depth. You will be part of a specialist team building novel pricing models, exploring alternative data sources, and shaping the next generation of machine learning capability within a growing challenger product area.
The Company
They are a major UK digital insurer with a strong reputation for data‑driven decision making. With millions of customers and significant recent investment in pricing, modelling, and analytics, they operate one of the most advanced data science environments in the industry. The business continues to scale rapidly, backed by strong financial performance and a culture that values curiosity, experimentation, and continuous improvement.
The Role
- Build predictive models to improve pricing, customer selection, and risk understanding across car and van insurance.
- Explore and engineer novel data sources to create innovative rating factors and alternative pricing strategies.
- Develop footprint and geospatial modelling approaches, as well as residual modelling to compare expected versus actual claims outcomes.
- Work with large, messy data sets to uncover complex patterns and drive commercially meaningful insights.
- Mentor junior colleagues.
Your Skills and Experience
- Strong commercial experience building predictive models in Python and SQL.
- Confident working with large, complex, or messy datasets.
- Experience applying machine learning techniques such as gradient‑boosted models, with exposure to tools like XGBoost or CatBoost.
- Ability to form structured analytical approaches, make sensible assumptions, and communicate your reasoning clearly.
- Comfortable mentoring others and contributing to a cooperative team environment.
What They Offer
- Salary between £60,000 and £75,000.
- £5,000 cash allowance.
- Hybrid working with one day a week in the office.
- Excellent progression opportunities within a high‑growth, high‑visibility team.
- A comprehensive benefits package.
How to Apply
If you are interested in this Senior Data Scientist position, please apply with your CV below or email me at
To Apply for this Job Click Here
Senior Data Scientist
Leicester
£65000 - £80000
+ Data Science & AI
PermanentLeicester, Leicestershire
To Apply for this Job Click Here
Senior Data Scientist, Alternative Pricing
Leicester
You will work on complex pricing and customer selection problems, using modern machine learning and huge, messy datasets to shape how millions of customers are priced and selected.
The Company
They are a well-established UK general insurance provider with a strong focus on car, van, bike and home insurance. Data science and analytics sit at the core of their strategy, supported by significant investment in cloud technology and digital platforms. Their pricing and data science capability is regarded as one of the strongest in the UK insurance market. You will join a profitable, tech enabled organisation with the scale, data and backing to do cutting edge work.
The Team
You will join a specialist Alternative Pricing Product team that sits alongside a core pricing function. It is a small, collaborative team of around six people, where you will provide technical leadership and mentor a graduate data scientist.
The Role
As a Senior Data Scientist, you will:
- Focus on pricing and customer selection for car and van insurance within the Alternative Pricing Product team.
- Build predictive models that identify new ways to set prices and select customers, beyond traditional pricing approaches.
- Work with very large, messy datasets across multiple product lines, leading data exploration, cleaning and feature engineering.
- Deploy models into production using Python, SQL, Azure ML and an internal deployment platform.
- Collaborate with pricing, risk and product stakeholders to test ideas, run experiments and influence pricing strategy.
- Mentor junior team members and contribute to setting technical standards within the team.
Your Skills And Experience
You will bring:
- Strong commercial experience as a Data Scientist or in a similar analytics role working on predictive modelling.
- Hands on experience building and deploying machine learning models using Python and SQL, ideally in a cloud environment such as Azure.
- Practical experience with tree based methods such as XGBoost or CatBoost, and an interest in geospatial or graph based modelling.
- Confidence working with large scale, messy, multi source datasets, including complex data cleansing and feature engineering.
- Experience solving pricing, risk or customer prediction problems and understanding how models drive profit, loss and customer outcomes.
How To Apply
If you are interested in this Senior Data Scientist opportunity in Alternative Pricing, please apply with your CV to be considered for the next stage of the process.
To Apply for this Job Click Here
Senior Insurance Data Scientist
£60000 - £75000
+ Risk Analytics
PermanentLeicestershire
To Apply for this Job Click Here
Senior Data Scientist
London or Leicester (hybrid, 1 day per week onsite)
£60,000 to £75,000
This is an opportunity to join a pricing team building innovative models that shape how pricing decisions are made. You will work with complex and novel datasets, develop predictive models, and help advance a modern modelling framework that delivers real commercial impact.
The Company
They are a well-established organisation investing in data science and advanced analytics. The pricing team operates with agility and encourages curiosity, experimentation and rapid learning. With strong leadership backing and a growing modelling roadmap, they are looking to add experienced Senior Data Scientists to support their next phase of development.
The Role
* Develop, refresh and combine pricing and footprint models that support pricing decisions.
* Work with messy, complex datasets including geospatial and alternative data sources.
* Build predictive and residual models across major products, contributing to a wider model chain.
* Review and improve existing early-stage models, progressing them toward production readiness.
* Explore new ways to manage and integrate multiple models within a stack.
* Guide a junior Data Scientist and support their technical development.
* Communicate model outputs clearly to technical and non-technical stakeholders.
Your Skills and Experience
* Strong experience working with large, messy and diverse datasets.
* Hands-on modelling experience using GLMs, XGBoost or similar predictive methods.
* Proficiency in Python and SQL, ideally within a cloud environment such as Azure.
* Experience combining or managing multiple models in a pipeline.
* Clear communication skills with the ability to explain insights effectively.
* A curious mindset and the ability to work at pace.
* Insurance experience is welcome but not essential.
What They Offer
* A salary between £60,000 and £75,000.
* Hybrid working with London or Leicester as a base.
* The chance to build impactful pricing and footprint models.
* Career development through ownership, visibility and coaching opportunities.
To Apply for this Job Click Here
Senior Actuarial Analyst
London
£50000 - £80000
+ Risk Analytics
PermanentLondon
To Apply for this Job Click Here
Senior Actuarial Analyst / Actuary
London, very flexible working
Salary 50000 to 80000
This is a rare opportunity to step into a highly autonomous role where you will own the capital modelling process for a growing insurance business. You will work closely with senior leaders, influence key decisions, and help build in‑house capability as the organisation scales.
The Company
They are a specialist insurer, established but growing and with a collaborative team. They combine a lean structure with strong technical expertise and a culture built around bright, driven people.
The Role
* Lead the development and ownership of capital modelling across the business
* Build models to assess risk, capital requirements and solvency positions
* Support Solvency II reporting and contribute to broader regulatory work
* Collaborate closely with pricing, actuarial and wider commercial teams to influence decisions
* Drive project work linked to business needs, solving complex problems with analytical approaches
* Play a key role as they transition capital models, solvency processes and actuarial reporting in‑house
Your Skills and Experience
* Strong commercial experience in capital modelling within insurance
* Understanding of Solvency II reporting and regulatory frameworks
* Partially or newly qualified actuary
* Coding capability such as Python, R or similar
* Experience in retail insurance
* Motivated, proactive and comfortable working independently in a fast‑paced environment
What They Offer
* Salary between 50000 and 80000 depending on experience
* Very flexible working, with the option to meet in London occasionally
* Study support for part‑qualified candidates
* High visibility across the business and genuine ownership of key modelling work
To Apply for this Job Click Here
Senior AI Engineer
City of London
£80000 - £90000
+ Data Science & AI
PermanentCity of London, London
To Apply for this Job Click Here
Senior AI Engineer
London – 1-2x week in office
Salary: £80,000 – £90,000
This is an exciting opportunity to join a business that is investing heavily in AI and modern cloud technologies. You will play a key role in building AI‑driven products that have a direct impact on customer experience, operational efficiency and the future of their platform.
The Company
They are a tech‑forward insurance organisation with a strong focus on delivering smarter, more personalised digital products. Their teams combine data, engineering and customer expertise to create solutions that simplify complex challenges for their users. Innovation, collaboration and a flexible working culture are at the heart of how they operate. They continue to scale their AI capability and are looking for someone who can help shape this next phase of growth.
The Role
In this AI Platform Engineer role, you will:
* Design, build and operate AI‑first products that deliver measurable value.
* Develop and deploy production‑grade AI agents on GCP using ADK, integrating with internal systems via REST and JSON APIs.
* Build and maintain robust evaluation and monitoring frameworks, including online and offline testing, A/B experiments and performance dashboards.
* Integrate AI agent functionality with applications through MCP servers and reliable tool configurations.
* Develop secure and scalable RAG pipelines, including ingestion, text processing, metadata handling and vector search in GCP.
* Embed security, compliance, GDPR controls and best‑practice engineering with clear documentation and stakeholder collaboration.
Your Skills and Experience
To be successful, you will bring:
* Strong Python skills for backend services, SDKs, API development, authentication and testing.
* Hands‑on experience working with LLMs, embeddings, prompt engineering, tool calling and RAG design.
* Practical knowledge of GCP services including Vertex AI, Model Garden, BigQuery, Cloud Run and Google’s ADK.
* Experience with document and data processing using tools such as Apache Tika, plus storage or caching technologies like Postgres, Redis, GCS or BigQuery.
* Solid DevOps practices including CI/CD, Docker, observability and automated testing.
* A product‑led mindset with a strong understanding of security, IAM, auditability and defining success metrics.
What They Offer
* Opportunities to shape AI products from the ground up.
* A collaborative environment that encourages innovation and career progression.
How to Apply
If you are excited about building production‑ready AI systems and want to drive meaningful impact, please apply with your CV.
To Apply for this Job Click Here
Data Analyst
London
£45000 - £55000
+ Advanced Analytics & Marketing Insights
PermanentLondon
To Apply for this Job Click Here
DATA ANALYST
LONDON/OXFORD/HYBRID
UP TO £55,000
This is an exciting opportunity to join a growing analytics function where your SQL expertise will directly shape a major FCA redress programme. You will work on high‑impact regulatory initiatives, delivering accurate, high‑quality analysis that supports critical business decisions.
ROLES AND RESPONSIBILITIES:
The Data Analyst will:
* Support the FCA redress programme and associated regulatory activity
* Work with complaints‑related datasets and large‑scale data extracts
* Write, maintain and optimise SQL queries for analysis and reporting
* Produce accurate data outputs, extracts and reports for internal and external use
* Collaborate with analytics colleagues and wider business teams
* Work alongside Data Engineering teams as they build microservices supporting the scheme
YOUR SKILLS AND EXPERIENCE:
The ideal candidate will have the following skills and experience:
* Strong SQL skills used in day‑to‑day analytical work
* Ability to manipulate, wrangle and validate large datasets
* Experience handling high‑volume data extract requests
* High attention to detail, especially in regulatory or accuracy‑critical work
* Experience with Tableau or similar visualisation tools
* Financial services or regulated‑environment experience is beneficial
* Car finance knowledge is a plus
APPLY BELOW!
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.
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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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