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 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
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
Senior Pricing Analyst
London
£49000 - £50000
+ Risk Analytics
PermanentLondon
To Apply for this Job Click Here
Senior Pricing Analyst
£50,000
London – Hybrid
Harnham are working with a growing insurance provider as they look to hire a Senior Pricing Analyst to support the development of robust pricing strategies across their travel insurance products.
THE COMPANY
- A growing UK insurance business known for its customer-focused approach and supportive working culture.
- Operating across a range of consumer products with a strong emphasis on innovation and data-led decision‑making.
- Recent investment and expansion mean strong opportunities for progression and development.
THE ROLE
You will play a key part in developing pricing strategies, analysing performance, and supporting commercial teams with insight-driven recommendations.
Specifically, you can expect to be involved in:
- Building and refining pricing models for insurance products.
- Analysing large data sets to identify trends, customer behaviour and pricing opportunities.
- Contributing to market and competitor analysis to support pricing decisions.
- Producing clear reports and presenting findings to senior stakeholders.
- Supporting forecasting activity and ensuring pricing practices align with regulatory standards.
YOUR SKILLS AND EXPERIENCE
- Strong analytical skills with experience using tools such as Excel, SQL, R or Python.
- Ability to communicate technical insights clearly to non-technical audiences.
- Experience in a pricing, analytics or financial role (insurance experience beneficial).
- Understanding of statistical modelling techniques, including GLMs.
- Highly detail-oriented and confident working across multiple projects.
THE BENEFITS
- Holiday allowance with incremental increases based on tenure.
- Core insurance and wellbeing benefits.
- Performance-related bonus scheme.
- Flexible hybrid working arrangements.
- Regular team events and professional development support.
THE PROCESS
- Initial 30‑minute interview.
- Technical stage focused on analytical capability.
- Final interview with senior stakeholders.
HOW TO APPLY
Please register your interest via the apply link on this page.
To Apply for this Job Click Here
Pricing Manager – Insurance
London
£70000 - £80000
+ Risk Analytics
PermanentLondon
To Apply for this Job Click Here
PRICING MANAGER- INSURANCE
£70-80K DEPENDING ON EXPERIENCE
LONDON BASED
This is an exciting opportunity to join a growing business in the insurance space where you can make a real impact on the business. You’d be able to work across a range of pricing analytics projects with the rare opportunity to really take ownership of your work and make an impact.
THE COMPANY
Our client are an exciting insurance business that are growing well. They’ve gone from strength to strength in recent years and this role is part of their increased presence in the market. You’d be able to work in small team within this hands-on, analytical role whilst also taking on management of a couple of analysts.
THE ROLE
- End-to-end development of some of their first GBM models across the book
- Develop and implement pricing strategies to enhance business performance
- Analyse large sets of customer data to drive insight and commercial performance across their pricing quotes
- Share insight with the wider team and helping to improve profitability across the business
- Manage a team of 2, helping with their development and progression
YOUR SKILLS AND EXPERIENCE:
- Essential to have experience within UK general insurance
- Essential to have had experience building GLM pricing models, ideally using ML techniques
- Exposure to both retail and risk pricing
- Good knowledge of programming software such as SAS, SQL, Python or R
- Experience managing junior analysts OR proven ability in coaching and leadership
SALARY AND BENEFITS
- Base salary £70-80,000 depending on experience
- Bonus
- Contributory pension scheme
- Work abroad scheme
- Private medical
- 25 days holiday
HOW TO APPLY
Please register your interest by sending your CV to Rosie Walsh through the ‘Apply’ link
To Apply for this Job Click Here
AI Platform Engineer
City of London
£70000 - £90000
+ Data Science & AI
PermanentCity of London, London
To Apply for this Job Click Here
Principal AI Platform Engineer
London
This is a standout opportunity to join a digital‑first insurer that is scaling an entirely new AI function. You will be the first permanent hire into a growing division, giving you direct ownership of production AI systems, end‑to‑end agentic automation, and the technical direction of a brand‑new platform.
The Company
They are a tech‑led insurer transforming how complex home insurance is delivered. Their vision is to become the UK’s first fully AI‑driven insurer, supported by modern cloud infrastructure and a collaborative product‑focused culture.
The Role
You will play a lead role in shaping, building, and scaling their AI platform, working closely with an AI Product Manager and senior leadership. Your work will focus on making AI production‑ready, highly scalable, and reliable across the business.
Key responsibilities include:
* Designing and delivering an AI platform that supports large‑scale agentic automation and end‑to‑end claims journeys
* Building robust RAG pipelines, LLM‑based systems, and deployment frameworks
* Developing AI agents for claims handling, internal tooling, and customer‑facing chat solutions
* Evolving an internal AI assistant and expanding its capabilities across teams
* Working hands‑on across cloud infrastructure, observability, evaluation, and optimisation
* Collaborating with engineering, product, and operations teams to take roadmap concepts into production
Your Skills and Experience
* Strong commercial experience in AI engineering or software engineering with a focus on LLMs and production AI systems
* Expertise in deploying AI models and agents at scale, including RAG, embeddings, and LLM tooling
* Hands‑on cloud engineering experience, ideally in GCP and its AI ecosystem
* Strong Python engineering ability and experience building production‑grade services
* Experience working with vector search, data ingestion, observability, and experimentation frameworks
* A STEM background or equivalent technical capability
What They Offer
* Salary up to 90,000 plus benefits
* Hybrid working with 1-2 days per week in their Sheffield office
* The chance to join as the first hire in a scaling AI division with a 10‑role roadmap
* Significant autonomy, influence, and end‑to‑end ownership of AI platform design
* The opportunity to build cutting‑edge agentic systems and production AI from the ground up
How to Apply
If you are excited by the opportunity, please apply with your CV.
To Apply for this Job Click Here
Pricing Analyst (Insurance)
£30000 - £40000
+ Risk Analytics
PermanentEssex
To Apply for this Job Click Here
PRICING ANALYST (INSURANCE)
£40,000
EAST ENGLAND (CAN BE REMOTE BASED WITH OCCASIONAL TRAVEL)
This is an exciting opportunity to join a growing business in the insurance space where you can make a real impact on the business. You’d be able to work across a range of pricing analytics projects, within a small team to really take ownership of your work and the wider team.
THE COMPANY
Our client are an exciting insurance business that are growing well. They’ve gone from strength to strength in recent years and this role is part of their increased presence in the market. You’d be able to work in a close-knit and focused team there with a focus on data and pricing.
THE ROLE
- Work on rate-changes, pricing adjustments and data-led pricing structures
- Refresh, validate and develop risk pricing models for new and current offerings
- Work with aggregators and market analysis to understand trends and customer behaviours
- Develop and implement competitive pricing strategies
YOUR SKILLS AND EXPERIENCE:
- Minimum 1 year experience within insurance or wider financial services OR a placement year in the same area
- Experience in pricing models or strategy is highly desirable
- Experience using SAS/SQL/Python or R
- Strong communication skills and desire to ‘hit the ground running’
SALARY AND BENEFITS
- Up to £40,000 base salary
- Discretionary bonus scheme
- Contributory pension scheme
- Hybrid work model
- 25 days holiday
HOW TO APPLY
Please register your interest by sending your CV to Rosie Walsh through the ‘Apply’ link
To Apply for this Job Click Here
Pricing Analyst
£35000 - £40000
+ Risk Analytics
PermanentEssex
To Apply for this Job Click Here
Technical Pricing Analyst
Salary
£30,000-£40,000
Location + work pattern
Office is in Essex but this is Remote role (some travel required), also open to candidates that want to work on a hybrid structure.
Overview
Harnham are working with a fast-growing insurance provider seeking a Technical Pricing Analyst to join their expanding pricing team. This is an excellent opportunity for someone early in their career who wants strong technical exposure and rapid development.
THE COMPANY
- A specialist insurance business undergoing significant growth and investment.
- Known for its ethical approach, strong customer reputation and focus on supporting underserved customer groups.
- A collaborative, personable environment with a flat structure and increasing autonomy for analysts.
THE ROLE
This role sits within the risk pricing team, supporting the development, enhancement and implementation of pricing models across multiple brands. You will work closely with experienced analysts to refresh existing models and contribute to rate changes and pricing improvements.
Specifically, you can expect to be involved in:
- Supporting the development and refresh of risk pricing models.
- Carrying out rate reviews and helping implement pricing changes.
- Working with senior analysts to improve model performance and pricing accuracy.
- Applying coding skills to manipulate, analyse and validate data.
- Contributing to the development of pricing tools and processes.
YOUR SKILLS AND EXPERIENCE
- 1-2 years of experience in a data, pricing or analytical role (including placement year experience).
- Strong numerical background, ideally with a degree in a mathematical, numerical or analytical subject.
- Coding skills in SAS, Python or SQL.
- Experience in insurance or financial services is highly beneficial.
- Understanding of risk modelling or rate-change analysis is advantageous.
- Strong analytical mindset and ability to communicate findings clearly.
THE BENEFITS
- Growing, modern insurance business with significant investment behind its expansion.
- Supportive culture with high autonomy and opportunities for early ownership.
- Flat structure and close collaboration with experienced pricing leaders.
- Real progression pathway to take ownership of models over time.
THE PROCESS
- Stage 1: Initial interview with members of the pricing team, including CV walk through, competency questions and technical pricing discussion.
- Stage 2: Technical interview involving a scenario or presentation of a previous piece of work.
HOW TO APPLY
Please register your interest via the apply link on this page.
To Apply for this Job Click Here
Lead AI Engineer
Sheffield
£80000 - £90000
+ Data Engineering
PermanentSheffield, South Yorkshire
To Apply for this Job Click Here
Lead AI Engineer
£80,000 – £90,000
Sheffield (Hybrid, 1-2 days a week)
A rare opportunity to step into a Lead level role where you will shape a new AI function and play a direct role in transforming how a digital insurer operates. You will build production grade AI systems, influence architecture, and drive agentic automation with a clear path to impact and visibility.
THE COMPANY
They are a technology driven insurance provider specialising in complex and non-standard home risks. Their model blends advanced AI capability with digital platforms to deliver a faster, smarter customer experience. You would be one of the first hires into this team, joining at a genuinely pivotal moment
THE ROLE
As a Lead AI Engineer you can expect to be involved in the following:
- Build production-ready AI agents on GCP using modern frameworks and Google’s ADK.
- Develop scalable RAG pipelines spanning ingestion, text processing and vector search.
- Integrate AI systems into policy, claims and CRM platforms through REST and JSON APIs.
- Implement monitoring, evaluation, A/B testing and cost or latency dashboards.
- Contribute to broader AI architecture and help shape engineering patterns and strategy.
- Work closely with engineering, ML Ops and data teams to bring models and prototypes into stable, scalable production.
SKILLS AND EXPERIENCE
The successful Lead AI Engineer will have the following skills and experience:
- Strong commercial experience in AI engineering, ML engineering, data engineering or software engineering with applied AI delivery.
- Deep expertise in GCP including Vertex AI, BigQuery, Cloud Run or Functions and related tooling.
- Strong Python skills and experience developing APIs and production AI systems.
- Hands on experience with LLMs, embeddings, RAG, vector databases and retrieval frameworks.
- Familiarity with LangChain, LangGraph or similar agentic frameworks.
- Solid engineering fundamentals including Docker, Kubernetes and CI/CD.
BENEFITS
The successful Lead AI Engineer will receive the following benefits:
- Salary between £80,000 – £90,000 – depending on experience
- Hybrid working with 1-2 office days in Sheffield.
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
AI Engineer
Sheffield
£70000 - £90000
+ Data Science & AI
PermanentSheffield, South Yorkshire
To Apply for this Job Click Here
Principal AI Engineer – Sheffield (1-2 days a week)
GCP REQUIRED
We are working with a growing, tech-driven insurance company looking for an AI Engineer to help build and deploy production-grade AI systems. You’ll play a key role in shaping AI‑first products, developing end‑to‑end agents, and creating robust evaluation and monitoring frameworks.
Responsibilities:
- Build and operate AI-powered products that deliver measurable outcomes.
- Develop production-ready AI agents on GCP, including secure API integrations.
- Integrate agent capabilities into applications using MCP servers and supporting tools.
- Develop reliable RAG pipelines, including ingestion, chunking, metadata and vector search.
Required:
- Strong Python skills for backend, APIs, testing and async patterns.
- Practical experience with LLMs, embeddings, prompt/function calling and vector databases.
- Solid knowledge of GCP services (Vertex AI, BigQuery, Cloud Run/Functions) and Google’s ADK.
- Experience with document processing, text normalisation and storage systems (Postgres, Redis, GCS/BigQuery).
- Familiarity with DevOps practices: Git, CI/CD, Docker, observability and automated testing.
- A product-focused mindset and the ability to translate needs into intuitive AI workflows.
To Apply for this Job Click Here
AI Research Engineer
London
£60000 - £70000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
AI Research Engineer
London (Hybrid – 2 days in office)
Competitive salary between £60,000 – £70,000 + bonus and benefits
This is a great opportunity for an AI Research Engineer who wants to work on applied AI. You will be joining a newly created AI function with investment and a clear mandate to transform how a specialist insurer operates using LLMs, agents, and automation across the claims journey.
The Company
They are a UK-based, digitally led specialist home insurer with a strong focus on complex and non-standard insurance. Technology, data, and AI are at the heart of how they operate, with a culture that feels closer to a tech company than a traditional insurer. Following recent investment, they are midway through a multi-year growth and transformation cycle where AI is a core strategic priority. You will be joining at a time when the AI team is growing, the roadmap is ambitious, and there is space to shape how things are done.
The Role
As an AI Research Engineer, you will sit within a small but rapidly scaling AI team, working alongside an AI Platform Engineer and reporting into the Head of AI. Your focus is on applied AI/ML research, fast experimentation, and turning ideas into working prototypes that can be adopted by the business.
You will:
- Rapidly prototype, test, and compare LLMs and embeddings for real product and claims use cases.
- Build features and enhancements for AI-first internal products, including their internal AI agent used by operations teams.
- Develop AI agents that support claims automation.
- Design, build, and improve evaluation frameworks.
- Run ongoing testing and monitoring.
- Work closely with Claims Operations and product stakeholders.
Your Skills And Experience
You will succeed in this role if you have:
- Strong Python engineering skills for backend services and API integrations.
- Hands-on experience working with LLMs and related tooling, including:
- LLMs RAG patterns, vector databases, function calling, and prompt design.
- Solid experience with Google Cloud Platform, ideally including:
- Vertex AI, Model Garden, BigQuery, Cloud Run or Cloud Functions
- Ability to turn ideas and problem statements into working prototypes that can be demonstrated to non-technical stakeholders.
- Strong collaboration skills, with experience working closely with operations or product teams to validate AI behaviour and refine solutions.
What They Offer
- Competitive salary plus annual bonus and comprehensive benefits package.
- Hybrid working
- The chance to join an AI function at an early stage, with direct access to the Head of AI and significant influence over tools, practices, and roadmap.
- Real ownership of impactful projects, with a clear link between your work and business outcomes in claims and operations.
- Ongoing professional development, including opportunities to broaden into AI product, platform, or leadership as the team scales.
How To Apply
Please register your interest by sending your CV to Madison Barlow via the Apply link on this page.
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
Data Engineer
Charlotte
$126016.2 - $147018.9
+ Data Engineering
PermanentCharlotte, North Carolina
To Apply for this Job Click Here
Senior Data Engineer
Location: Charlotte, NC
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
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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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