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.
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.
HIRING DATA SCIENTISTS?
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.
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
Ops Analytics Manager
London
£70000 - £85000
+ Advanced Analytics & Marketing Insights
PermanentLondon
To Apply for this Job Click Here
Ops Analytics Manager – High-Growth InsurTech | £70-85k | Hybrid (London)
A rapidly scaling InsurTech business is seeking an Operations Analytics Manager to lead a critical function delivering insights to clients and supporting internal operations. With recent funding secured and plans to double headcount this year, this is a unique opportunity to join early and shape the future of data and reporting in a tech-forward environment.
The Role
This position sits at the intersection of operations, product, and data. You’ll take ownership of client-facing analytics, internal performance reporting, and drive improvements to the data platform and reporting experience.
Key responsibilities:
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Lead operational and client reporting efforts, ensuring insights are timely, accurate, and actionable
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Be the primary contact for queries relating to client reports and data outputs
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Support the operations team with performance analytics and insight generation
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Collaborate closely with product and data to develop a live reporting portal (e.g. Metabase)
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Manage and mentor a small team of analysts
Tech Environment
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Analytics: Tableau, SQL
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Engineering: dbt, Python, Postgres, Azure, Prefect
✅ Ideal Candidate
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4-6 years’ experience in analytics, with some leadership exposure
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Proven skills in SQL, Python, and dbt
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Experience delivering operational insights and improving reporting processes
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Comfortable working cross-functionally with data, ops, and product teams
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Strong attention to detail and ability to work in a fast-paced environment
Location & Flexibility
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Hybrid: ~2-3 days per week in a Central London office (flexible)
Salary & Package
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£70,000 – £85,000 + benefits + equity
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Fast-track growth in a well-funded, high-impact environment
❌ Sponsorship unavailable
Urgent hire – interviewing immediately
Interested? Send CVs directly to the recruitment contact.
To Apply for this Job Click Here
Head of Data Platform
New Malden
£95000 - £110000
+ Data Engineering
PermanentNew Malden, London
To Apply for this Job Click Here
HEAD OF DATA PLATFORM
LONDON
£110,000
THE COMPANY
Backed by AXA and powered by smart tech, this company provider is transforming how the UK insures all types of homes. As they undergo a major data transformation, this role offers the chance to shape the data future of a mission-led, tech-forward insurer.
THE ROLE
As Head of Data Platform, you will lead the development and evolution of a modern, scalable data platform. With a major migration underway and ambitious plans to enable AI-driven insights across the business, this is a hands-on leadership role with strategic influence, architectural ownership, and real scope to shape the future of data at the company.
Specifically, you can expect to be involved in the following:
- Overseeing a small team of Data Engineers, with scope to build and upskill the function
- Leading and executing a data platform migration into Google Cloud Platform (GCP)-initially in partnership with a consultancy
- Owning all aspects of the data warehouse, ETL/ELT, and platform infrastructure (DevOps, FinOps)
- Driving forward best practices in data governance, access control, and architecture
- Collaborating cross-functionally with pricing, analytics, IT, and commercial teams
- Helping shape the long-term strategy and roadmap for platform evolution, including future capabilities like AI, Gemini, and self-serve analytics
SKILLS AND EXPERIENCE
The successful Head of Data Platform will have the following skills and experience:
- Strong hands-on background in data engineering, with 5+ years working on modern data platforms
- Experience leading cloud data migrations-GCP and BigQuery strongly preferred
- Proficiency in SQL, Python, dbt, Airflow, Terraform and other modern tooling
- Excellent understanding of data architecture, governance, and DevOps best practices
- Proven leadership or team management experience within a regulated or mid-to-large tech-driven company
- Comfortable being both strategic and hands-on in a fast-moving, evolving environment
BENEFITS
The successful Head of Data Platform will receive the following benefits:
- Salary up to £110,000
- Performance-based bonus
- Hybrid working, 2/3 days in South West London
- 25 days annual leave + bank holidays
- Pension scheme
- Private medical and life insurance
- Training and development opportunities
- Impactful work at the core of a business with a clear social mission
HOW TO APPLY
Please register your interest by sending your resume/CV to Joana Alves via the Apply link on this page.
To Apply for this Job Click Here
Head of Data Platform
£100000 - £110000
+ Data Engineering
PermanentSurrey
To Apply for this Job Click Here
HEAD OF DATA PLATFORM
SURREY – 3 DAYS PER WEEK IN OFFICE
£100,000 – £110,000 + BENEFITS
Are you an experienced and visionary data leader with a proven track record in building and scaling robust data platforms? This is a unique opportunity to join a leading specialist insurance provider that’s disrupting its market by covering non-standard and hard-to-insure properties.
THE COMPANY:
Our client is a well-established and growing specialist insurance provider focusing on unique and challenging properties often overlooked by traditional insurers. They leverage smart technology to offer quick, comprehensive quotes and are backed by one of the UK’s largest insurers. With an “Excellent” Trustpilot rating and awards for transparency, they pride themselves on customer satisfaction and value. They offer a supportive and innovative environment where you can make a real impact.
THE ROLE:
As the Head of Data Platform, you will be pivotal in shaping the company’s data strategy and infrastructure. Reporting to the Head of Data Science and Analytics, you’ll lead a small team of Data Engineers, with significant influence over its growth and development.
Initially, your focus will be on a critical green/brownfield migration project, taking full ownership of the data platform, including the core data warehouse and all associated ETL/ELT processes. This is a highly hands-on role where you’ll contribute to architectural design, strategic roadmap development, and data engineering tasks.
Longer-term, you’ll establish DevOps and FinOps best practices, ensure robust governance, and lead the exciting integration of AI capabilities into the modern data platform. You’ll also be empowered to suggest new tools and strategies to continuously enhance the company’s data capabilities.
YOUR SKILLS AND EXPERIENCE:
The ideal Head of Data Platform will have:
- Extensive experience with Google Cloud Platform (GCP), particularly BigQuery
- Proficiency with a modern data tech stack, including SQL, Python, Airflow, dbt, Dataform, Terraform
- Experience in a mid-large sized company within a regulated industry, with a strong understanding of data governance.
- A strategic mindset, leadership skills, and a hands-on approach.
HOW TO APPLY:
Please send your CV via the Apply link on this page.
To Apply for this Job Click Here
Senior Pricing Analyst
London
£35000 - £45000
+ Risk Analytics
PermanentLondon
To Apply for this Job Click Here
PRICING MODELLING ANALYST
UP TO £45,000
REMOTE (London)
This is an exciting opportunity to take ownership of the pricing models and innovate and refresh predictive models within this companies predictive modelling suite.
THE COMPANY
This company is an exciting, growing business in the insurance space, offering an array of home insurance products.
THE ROLE
You will be doing the following daily:
- Develop, innovate, and update predictive models within the retail pricing system.
- Ensure models directly impact pricing, enhance customer experience, and boost commercial performance.
- Run split tests on existing models, track results, and recommend improvements.
- Work with the Senior Pricing Analyst to adjust price selection logic based on trading performance.
- Coordinate with Retail Pricing, Technical Pricing, Data Science, Software Engineering, and Marketing teams to provide insights that drive business performance.
- Utilize SQL for data access and Python for data processing, modeling, and pricing.
- Work within custom-built software for optimal price setting, rather than relying on standard price tools.
- Analyse data from millions of quotes to identify revenue growth opportunities through pricing strategies.
- Operate in a fast-paced setting, implementing frequent price adjustments and observing results quickly.
- Collaborate with software developers to adapt and optimize the pricing tools based on identified market opportunities
YOUR SKILLS AND EXPERIENCE
- Previous modelling experience in an insurance setting is ideal.
- Strong Python skills are desirable.
- Highly analytical.
- Numerate degree from a Russel Group university.
- Excellent written and verbal communication skills.
THE BENEFITS
- Up to £45,000.
- Flexible working, mostly hybrid.
- Discretionary bonus.
HOW TO APPLY
Please register your interest by sending your CV to Gaby Adamis via the Apply link on this page.
To Apply for this Job Click Here
Senior Software Engineer (Python)
London
£100000 - £110000
+ Data Engineering
PermanentLondon
To Apply for this Job Click Here
Role: Senior Software Engineer (Python)
Salary: £100,000-£110,000 + Bonus
WFH: Hybrid – 2-3 days/week in-office (Central London)
Overview
Our client is a profitable and fast-growing UK fintech helping over 800,000 customers improve their financial health. Backed by strong leadership and AI-driven innovation, the company is building a brand-new mobile app and scaling its engineering team to support rapid product delivery.
They’re now hiring a Senior Python Engineer to join this lean, high-impact team and help shape the future of fair, tech-driven credit products.
Key Responsibilities
- Design, build and scale modern APIs and backend services in Python
- Lead technical delivery across greenfield and legacy systems
- Collaborate closely with product and DevOps teams
- Write maintainable, testable, high-performance code
- Influence architecture and mentor junior engineers
- Balance delivery with strategic thinking in a fast-moving environment
Ideal Candidate
- 7+ years of experience in software engineering
- Strong Python (FastAPI, Flask, or Django preferred)
- AWS or Azure cloud exposure
- Frontend awareness (e.g. React)
- Agile mindset; thrives in lean, delivery-focused teams
- Passionate about AI and emerging tech
- Holds a STEM degree (Russell Group or Red Brick ideal)
- UK, ILR or Settled Status required (no sponsorship available)
Benefits
- Up to £110,000 base salary
- Company bonus scheme
- Hybrid working (2-3 days/week in-office)
- 25-30 days holiday + bank holidays
- Enhanced pension & life cover
- Ongoing training and mentoring
- Inclusive, ambitious team culture
Interview Process
- HR Intro + CV Review
- Technical Deep Dive
- Python Task or Design Challenge
- Final with CEO + Leadership (vision & ambition focus)
This is a rare chance to join a profitable fintech scaling fast – and help redefine access to fair financial products in the UK.
To Apply for this Job Click Here
Ops Analytics Manager
London
£70000 - £85000
+ Advanced Analytics & Marketing Insights
PermanentLondon
To Apply for this Job Click Here
OPS ANALYTICS MANAGER – LONDON
UP TO £85,000
THE COMPANY
A high-growth InsurTech business is seeking an Operations Analytics Manager to lead a key function to drive their continued growth.
THE ROLE
The successful Ops Analytics Manager responsibilities will include:
- Utilise SQL and Python to extract, transform, and analyse data from various sources to provide actionable insights
- Develop and maintain robust analytics frameworks to monitor and improve operational efficiency across different departments
- Collaborate closely with cross-functional teams to understand business needs and translate them into data-driven solutions
- Design and implement dashboards and reports to visualize KPIs and performance metrics
- Support senior management with strategic decision-making by presenting clear, concise findings derived from complex data sets
YOUR SKILLS AND EXPERIENCE
The successful Ops Analytics Manager will have the following skills and experience:
- Proven experience in a similar role focusing on operational analytics and data-driven decision-making
- Strong proficiency in SQL and Python for data extraction, manipulation, and analysis
- Excellent communication skills with the ability to present technical concepts to non-technical stakeholders
THE BENEFITS
The successful Ops Analytics Manager will receive a salary of up to £85,000, plus an array of additional benefits.
HOW TO APPLY:
Please register your interest by sending your CV to Harry Mincer via the apply link below.
To Apply for this Job Click Here
Data Scientist
London
£70000 - £80000
+ Data Science & AI
PermanentLondon
To Apply for this Job Click Here
Data Scientist
Up to £80,000
London (Hybrid)
Company:
They are an AI-driven climate risk analytics platform that partners with businesses within Insurance, Private Equity, Asset Management and governments to understand and prepare for the physical and transitional impacts of climate change.
Responsibilities:
- Research and implement loss models that quantify climate-related risks, focusing on robustly estimating asset vulnerabilities.
- Calibrate and validate loss models against a wide variety of data sources, both qualitatively and quantitatively to ensure they meet rigorous scientific standards.
- Contribute to building our overall loss modelling framework, ensuring robustness and adaptability across diverse client requirements and geographies
- Model documentation and presentations to engage with stakeholder and customers, all while representing the team at international conferences and industry events
Requirements:
- MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields.
- 3+ years of experience in a Data Science, Data Analysis, or related role
- Strong hands-on experience with Python and SQL
- Excellent communication skills and stakeholder engagement ability
How to Apply:
Please register your interest by sending your CV to Emily Burgess via the Apply link on this page
To Apply for this Job Click Here
Data Scientist – Insurance
New York
$60 - $80
+ Data Science & AI
ContractNew York
To Apply for this Job Click Here
Data Scientist – Insurance Analytics
Remote (10 am-6 pm EST)
6-Month Contract to Hire
$60-80/hr
About the Role
Our client, a specialized provider in the non-standard insurance space, is seeking a highly analytical and hands-on Data Scientist for a 6-month contract-to-hire position. This role is ideal for someone with 3-5 years of experience in data science or actuarial analytics, particularly within insurance domains. The successful candidate will have a strong foundation in predictive modeling, machine learning, and insurance business applications such as loss modeling, retention analysis, and close rate modeling.
Key Responsibilities
- Build and maintain predictive models focused on loss prediction, retention, and close rates.
- Leverage machine learning techniques, including time series analysis and unsupervised learning, to uncover patterns in complex insurance data.
- Perform data wrangling to clean, merge, and transform datasets from multiple internal and external sources.
- Conduct inferential statistical analysis to support underwriting, pricing, and business strategy decisions.
- Collaborate with actuarial, underwriting, and business teams to translate data insights into actionable recommendations.
- Monitor model performance over time and support ongoing model validation and recalibration efforts.
- Develop compelling data visualizations and dashboards (preferably in Power BI; Tableau experience also acceptable).
- Communicate findings through strong data storytelling and synthesis, tailored to both technical and business audiences.
Required Skills & Experience
- 3-5 years of experience as a Data Scientist, preferably within insurance, actuarial analytics, or related domains.
- Strong programming and data skills:
- Python, SQL, and R
- Proven experience with data wrangling and ETL workflows
- Expertise in predictive modeling and machine learning, particularly for insurance applications
- Solid foundation in inferential statistics, unsupervised learning, and time series modeling
- Experience working with insurance data, including claims, underwriting, policy, and exposure data
- Strong experience in data visualization using Power BI or Tableau
- Ability to present technical results clearly and persuasively to business stakeholders
Nice to Have
- Experience in non-standard auto or specialty insurance lines
- Progress toward actuarial exams (SOA or CAS)
- Familiarity with cloud data environments (e.g., AWS, Azure)
To Apply for this Job Click Here
Graduate Software Engineer
London
£40000 - £50000
+ Data Engineering
PermanentLondon
To Apply for this Job Click Here
Role: Graduate Software Engineer – Full Stack
Salary: £40,000 -£60,000
Location: Central London – 4 days per week in-office
Overview
Our client is a rapidly growing digital insurance provider on a mission to simplify and modernise the insurance experience. Backed by £43m in funding and with over 300,000 customers, they’re entering a key period of product expansion. They’re looking for a Software Engineer (Full Stack) to help shape and scale their platform as they continue to grow.
Key Responsibilities
- Deliver high-impact features and lead cross-functional projects
- Collaborate with Product, Data, and Commercial teams to build user-first solutions
- Tackle meaningful, end-to-end challenges across the stack
- Influence platform architecture and engineering practices
- Maintain strong standards through testing, peer reviews, and clean code
- Contribute to product and team direction in a high-growth environment
Ideal Candidate
- 1-3 years of full-stack engineering experience
- Comfortable across frontend and backend (Python and Angular preferred)
- Strong software engineering fundamentals and a quality-focused mindset
- Experience working collaboratively in cross-functional teams
- Curious, proactive, and excited by ownership and pace
- Strong communicator who values team culture and clarity
Tech Stack / Tools
- Python (microservices)
- Angular (modern) (Open to React, Vue, Next.js and others)
- Russell Group University Graduate (Computer Science or STEM Degree)
Benefits
- Rapid progression
- 25 days holiday + public holidays
- Dedicated development budget & senior mentoring
To Apply for this Job Click Here
Graduate Software Engineer
London
£35000 - £40000
+ Data Engineering
PermanentLondon
To Apply for this Job Click Here
GRADUATE SOFTWARE ENGINEER
LONDON
£40,000
THE COMPANY
This fast-growing digital insurance scaleup is transforming the industry with a customer-first approach-bringing simplicity, transparency, and affordability to rental, home, and travel insurance. With over 100,000 customers and ambitious plans to launch new products, your work here will directly shape how people protect the things they love most.
THE ROLE
As a Graduate Software Engineer, you will be hands-on in designing, building, and scaling products that redefine what modern insurance looks like. You’ll join a cross-functional pod of engineers and collaborate to solve real customer problems and influence product direction from day one.
Specifically, you can expect to be involved in the following:
- Building responsive web applications using Angular (modern)
- Developing scalable Python microservices, containerised with Docker
- Working on cloud infrastructure with Kubernetes on AWS
- Helping to expand the product portfolio during a key period of rapid growth
SKILLS AND EXPERIENCE
The successful Graduate Software Engineer will have the following skills and experience:
- Degree in Computer Science or another STEM field (1st or Distinction highly preferred)
- Demonstrated experience via GitHub, side projects, internships, or previous roles
- Effective communication and collaboration skills-this is a sociable, team-driven environment
- Passion for building simple, user-friendly products
- Fast learner with the ability to prioritise and work flexibly across multiple projects
BENEFITS
The successful Graduate Software Engineer will receive the following benefits:
- Salary up to £40,000
- Hybrid working, 4 days in the office, 1 WFH
- Benefits package
- Opportunity to learn and upskill in a high bar tech driven scale up
HOW TO APPLY
Please register your interest by sending your resume/CV to Joana Alves via the Apply link on this page.
To Apply for this Job Click Here
Senior React Native Developer
London
£90000 - £100000
+ Data Engineering
PermanentLondon
To Apply for this Job Click Here
Role: Senior React Native Developer
Salary: £100,000 + Bonus
WFH: Hybrid – 2-3 days/week in-office (Central London)
Overview
Our client is a fast-growing UK fintech on a mission to reshape the credit landscape through technology and innovation. With over 800,000 customers and a Trustpilot rating of 4.8, they’re entering an exciting new growth phase-investing heavily in tech and launching a brand-new mobile app in September 2025.
They’re now hiring a Senior React Native Developer to join a small, collaborative team and play a central role in delivering a high-performance mobile product. This is a hands-on opportunity to help shape an app used daily by thousands, reporting directly to the CTO.
Key Responsibilities
- Design, build, and support the flagship React Native mobile app
- Deliver scalable, reusable components and front-end libraries
- Translate UI/UX designs into performant, production-ready code
- Own releases for both iOS and Android platforms
- Work with native modules when required
Ideal Candidate
- 5+ years of mobile development experience with React Native
- Proven app delivery to iOS & Android app stores
- Strong understanding of mobile performance, architecture, and design patterns
- Solid grasp of domain-driven design, clean code principles, and MVC frameworks
- STEM or creative mobile app degree preferred
- High energy, confident communicator, team-first mindset
- Must have UK, ILR, or Settled Status (no sponsorship available)
Benefits
- £100,000 base salary
- Company bonus scheme
- Hybrid working (2-3 days/week in-office)
- 25-30 days holiday + bank holidays (increases with tenure)
- Enhanced pension + 4x life cover
Interview Process
- Behavioural & CV run-through
- Technical chat (scalability, architecture)
- Technical Deep Dive – Coding & technical Q&A
- Final with CTO + Engineering Lead
Join a profitable fintech scaling rapidly, and play a key role in launching one of the most ambitious financial apps in the UK this year.
To Apply for this Job Click Here
Pricing Data Scientist
London
£40000 - £65000
+ Risk Analytics
PermanentLondon
To Apply for this Job Click Here
PRICING DATA SCIENTIST
LONDON- HYBRID
UP TO £65,000
Join a fast-growing motor insurtech company, revolutionizing the insurance industry through data-driven insights, innovative pricing models, and cutting-edge technology. They are looking for a talented Pricing Data Scientist to join the dynamic team and drive innovation in motor insurance pricing.
THE ROLE
- Develop and refine pricing models using statistical and machine learning techniques to improve underwriting accuracy and risk assessment.
- Analyse large data sets to identify trends, customer behaviours, and risk factors that impact pricing strategies.
- Implement data-driven decision-making processes to enhance competitive pricing while maintaining portfolio profitability.
- Collaborate with actuarial, underwriting, product, and technology teams to develop and deploy innovative pricing strategies.
- Continuously monitor and evaluate model performance, making data-backed improvements as needed.
REQUIREMENTS
- Strong experience in data science, pricing analytics within insurance or fintech industries.
- Expertise in statistical modelling, machine learning, and data analysis techniques.
- Proficiency in programming languages such as Python, R, or SQL.
HOW TO APPLY
Please send CV below
To Apply for this Job Click Here
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FAQ:
What does a Data Analyst do in insurance?
- 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.
- 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.
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?
- 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.
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.
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.
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:
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.
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.
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.
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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