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
Cloud engineer
Paris
€50000 - €60000
+ Data & Technology
PermanentParis, Île-de-France
Nous recrutons pour une société dans le domaine de l’Assurance .
Missions:
En tant qu’Ingénieur Cloud au sein de notre équipe, vos missions comprendront :
- Concevoir, mettre en place et gérer l’architecture d’infrastructure dans le cloud (AWS)
- Automatiser le déploiement, la gestion et la mise à l’échelle des ressources cloud
- Refonte des processus et des outils de test
- Supervision globale des chantiers de sécurité
Profil Recherché:
Nous recherchons un Ingénieur Cloud possédant les compétences et les qualités suivantes :
- Expérience minimale d’1 à 2 ans sous AWS.
- Intérêt pour le secteur de l’assurance, avec une expérience dans ce domaine étant un plus.
- Compétences techniques incluant AWS, DevOps, Terraform. Connaissance de la sécurité (SRE), développement et Docker sont des avantages.
- Aptitudes comportementales incluant la curiosité, la passion, des compétences en communication argumentée, une sensibilisation à la culture de la sécurité et une attention aux détails.
Outils et Environnement Techniques:
- Architecture serverless hébergée sur AWS avec CloudFront, S3, API Gateway, Lambda, DynamoDB, SNS, SQS.
- Langages et frameworks incluant Vue.js pour le front-end et Python 3 pour le back-end.
- Outils de déploiement tels que Docker et Terraform pour l’infrastructure.
Langues:
- Français est obligatoire, l’anglais n’est pas nécessaire.
Intéressé(e) ?
Cloud DevOps Engineer
Paris
€45000 - €55000
+ Data & Technology
PermanentParis, Île-de-France
CLOUD DEVOPS ENGINEER
PARIS (75)
UP TO 55K€
Une startup innovante dans le domaine de l’assurtech recherche un Cloud DevOps Engineer pour rejoindre ses équipes et contribuer activement à son développement.
LES MISSIONS
Au sein d’une équipe tech d’une dizaine de personnes, vous serez responsable de la gestion des outils d’infrastructure.
Au quotidien, vous aurez pour mission de :
- Choisir l’infrastructure appropriée en fonction des contraintes de la plateforme IT
- Développer des pipelines robustes et fluides
- Garantir le bon déploiement des solutions en production (tests unitaires, A/B testing)
- Garantir constamment la sécurité de l’infrastructure
- Travailler sur divers projets en mode AGILE
VOTRE PROFIL
- Vous justifiez d’une expérience d’au moins 2 ans en DevOps, SRE ou sysadmin
- Excellente maîtrise du Cloud AWS, Python et Terraform
- Idéalement des connaissances sur Docker et/ou Kubernetes
- L’envie d’apprendre et de monter en compétences
POUR POSTULER
Merci de me faire part de votre CV et je vous recontacterai au plus vite.
Cloud DevOps Engineer
Paris
€45000 - €55000
+ Data & Technology
PermanentParis, Île-de-France
CLOUD DEVOPS ENGINEER
PARIS (75)
UP TO 55K€
Une startup innovante dans le domaine de l’assurtech recherche un Cloud DevOps Engineer pour rejoindre ses équipes et contribuer activement à son développement.
LES MISSIONS
Au sein d’une équipe tech d’une dizaine de personnes, vous serez responsable de la gestion des outils d’infrastructure.
Au quotidien, vous aurez pour mission de :
- Choisir l’infrastructure appropriée en fonction des contraintes de la plateforme IT
- Développer des pipelines robustes et fluides
- Garantir le bon déploiement des solutions en production (tests unitaires, A/B testing)
- Garantir constamment la sécurité de l’infrastructure
- Travailler sur divers projets en mode AGILE
VOTRE PROFIL
- Vous justifiez d’une expérience d’au moins 2 ans en DevOps, SRE ou sysadmin
- Excellente maîtrise du Cloud AWS, Python et Terraform
- Idéalement des connaissances sur Docker et/ou Kubernetes
- L’envie d’apprendre et de monter en compétences
POUR POSTULER
Merci de me faire part de votre CV et je vous recontacterai au plus vite.
Data Analyst
Leeds
£40000 - £42000
+ Data & Technology
PermanentLeeds, West Yorkshire
DATA ANALYST
Fully Remote, Leeds
Up to £40,000
The Company:
Working for a London-based insurer that specialises in home cover. They are experts at insuring people who are looking to build, rent, renovate or leave a home unoccupied. Their smart tech enables customers to get an instant online quote regardless of how complex the needs may be. The company values include believing that every unique home is well deserved of being protected by insurance and that is something they provide.
The team:
Joining the Claims Insight team, you will be working on the Claims data reporting into the Head of Data Science and Analytics. The wider data team is made up of engineers, analysts developers and you will be working in a fast-paced environment with a great team relationship. The way you work is flexible whether you want to work at home or in the office.
The role:
As a Data Analyst, you will be responsible for:
– Making sure the data is accessible, put into the right place, and understandable to all in the business.
– The data is currently very dirty so will need to clean and improve this
– Looking at the claims spend, the life cycle measures of claims, and volumetrics.
– Assuring the data is fed into underwriting and the reports are accurate.
– Producing reports daily, weekly and monthly for stakeholders to manage the claims performance
Skills/ Experience:
– Claims background (REQUIRED)
– Advanced SQL (REQUIRED)
– Tableau or Power BI (REQUIRED)
– R or Python (DESIRABLE)
Interview Process:
1st Stage- Teams meeting discussing CV background/experience
2nd Stage – Face-to-face interview, technical test and questions
CTO
Paris
€80000 - €120000
+ Data & Technology
PermanentParis, Île-de-France
CTO
UP TO 120K €
PARIS
présence minimum 3/4j par mois
Nous recrutons un CTO dans le domaine de l’assurance axée sur les opérations de back-office, vous serez responsable de la stratégie technologique, de la mise en œuvre des systèmes et de la supervision des opérations techniques pour soutenir les activités de l’assurance. Votre rôle principal consistera à diriger et à développer une équipe technique compétente pour garantir une infrastructure solide et des systèmes de back-office efficaces.
Responsabilités :
- Définir la vision technologique et la stratégie pour l’entreprise d’assurance, en tenant compte des besoins spécifiques aux opérations de back-office.
- Concevoir et mettre en œuvre des solutions technologiques adaptées pour soutenir les opérations de back-office de l’assurance, en automatisant les processus, en améliorant l’efficacité et en assurant la conformité réglementaire.
- Superviser les équipes techniques (internationales) responsables du développement, de la maintenance et de l’optimisation des systèmes de back-office, y compris les applications, les bases de données, les intégrations et les flux de données.
- Assurer la sécurité des données et la protection de la vie privée des clients en mettant en place des mesures de sécurité robustes et en veillant à la conformité aux réglementations en vigueur.
- Collaborer avec les autres départements de l’entreprise, tels que les opérations, la conformité et la gestion des risques, pour identifier les opportunités d’amélioration des processus et mettre en œuvre des solutions technologiques appropriées.
- Superviser les projets technologiques, en veillant à ce qu’ils soient livrés dans les délais et dans les limites du budget, tout en garantissant la qualité des livrables.
- Assurer une veille technologique continue pour identifier les tendances, les opportunités et les défis dans le domaine de l’assurance et des opérations de back-office.
- Gérer les relations avec les fournisseurs technologiques, en évaluant les partenariats et en négociant les contrats.
Compétences requises :
- Solide expérience dans le domaine de l’assurance, avec une compréhension approfondie des opérations de back-office et des processus d’assurance.
- Expérience éprouvée dans des rôles de direction technique, idéalement en tant que CTO ou responsable technique d’une entreprise d’assurance ou d’un secteur connexe.
- Connaissance approfondie des systèmes d’assurance, des flux de travail opérationnels et des réglementations applicables.
- Expérience dans la mise en œuvre et la gestion de systèmes de back-office, y compris les applications, les bases de données, les intégrations et les flux de données.
- Maîtrise des technologies et des outils pertinents pour les opérations de back-office, tels que les systèmes de gestion de police, les systèmes de réclamation, les outils de tarification, etc.
- Compétences avancées en matière de gestion de projet et de gestion d’équipe technique.
- Excellentes compétences en communication et en leadership, avec la capacité de collaborer
- Excellentes compétences dans les systèmes de gestion de contenu, les sites Web à fort volume de transactions, les centres d’appels, DevOps et CI/CD, les micro-services, l’infrastructure et les services cloud, les ITSM modernes.
Devops / Cloud engineer
Paris
€45000 - €80000
+ Data & Technology
PermanentParis, Île-de-France
Missions:
En tant qu’Ingénieur Cloud au sein de notre équipe, vos missions comprendront :
- Concevoir, mettre en place et gérer l’architecture d’infrastructure dans le cloud (AWS)
- Automatiser le déploiement, la gestion et la mise à l’échelle des ressources cloud
- Refonte des processus et des outils de test
- Supervision globale des chantiers de sécurité
Profil Recherché:
Nous recherchons un Ingénieur Cloud possédant les compétences et les qualités suivantes :
- Expérience minimale d’1 à 2 ans sous AWS.
- Intérêt pour le secteur de l’assurance, avec une expérience dans ce domaine étant un plus.
- Compétences techniques incluant AWS, DevOps, Terraform. Connaissance de la sécurité (SRE), développement et Docker sont des avantages.
- Aptitudes comportementales incluant la curiosité, la passion, des compétences en communication argumentée, une sensibilisation à la culture de la sécurité et une attention aux détails.
Outils et Environnement Techniques:
- Architecture serverless hébergée sur AWS avec CloudFront, S3, API Gateway, Lambda, DynamoDB, SNS, SQS.
- Langages et frameworks incluant Vue.js pour le front-end et Python 3 pour le back-end.
- Outils de déploiement tels que Docker et Terraform pour l’infrastructure.
Langues:
- Français est obligatoire, l’anglais n’est pas nécessaire.
Intéressé(e) ?
Cloud DevOps Engineer
Paris
€45000 - €55000
+ Data & Technology
PermanentParis, Île-de-France
CLOUD DEVOPS ENGINEER
PARIS (75)
UP TO 55K€
Une startup innovante dans le domaine de l’assurtech recherche un Cloud DevOps Engineer pour rejoindre ses équipes et contribuer activement à son développement.
LES MISSIONS
Au sein d’une équipe tech d’une dizaine de personnes, vous serez responsable de la gestion des outils d’infrastructure.
Au quotidien, vous aurez pour mission de :
- Choisir l’infrastructure appropriée en fonction des contraintes de la plateforme IT
- Développer des pipelines robustes et fluides
- Garantir le bon déploiement des solutions en production (tests unitaires, A/B testing)
- Garantir constamment la sécurité de l’infrastructure
- Travailler sur divers projets en mode AGILE
VOTRE PROFIL
- Vous justifiez d’une expérience d’au moins 2 ans en DevOps, SRE ou sysadmin
- Excellente maîtrise du Cloud AWS, Python et Terraform
- Idéalement des connaissances sur Docker et/ou Kubernetes
- L’envie d’apprendre et de monter en compétences
POUR POSTULER
Merci de me faire part de votre CV et je vous recontacterai au plus vite.
Data Analyst
Manchester
£40000 - £42000
+ Data & Technology
PermanentManchester, Greater Manchester
DATA ANALYST
Fully Remote, Manchester
Up tp £40,000
The Company:
Working for a London- based insurer that specialises in home cover. They are experts at insuring people who are looking to build, rent, renovate or leave a home unoccupied. Their smart tech enables customers to get an instant online quote regardless of how complex the needs may be. The company values include believing that every unique home is well deserved of being protected by insurance and that is something they provide.
The team:
Joining the Claims Insight team, you will be working on the Claims data reporting into the Head of Data Science and Analytics. The wider data team is made up of engineers, analysts developers and you will be working in a fast-paced environment with a great team relationship. The way you work is flexible whether you want to work at home or in the office.
The role:
As a Data Analyst, you will be responsible for:
– Making sure the data is accessible, put into the right place, and understandable to all in the business.
– The data is currently very dirty so will need to clean and improve this
– Looking at the claims spend, the life cycle measures of claims, and volumetrics.
– Assuring the data is fed into underwriting and the reports are accurate.
– Producing reports daily, weekly and monthly for stakeholders to manage the claims performance
Skills/ Experience:
– Claims background (REQUIRED)
– Advanced SQL (REQUIRED)
– Tableau or Power BI
– R or Python (Desirable)
Interview Process:
1st Stage- Teams meeting discussing CV background/experience
2nd Stage – Face-to-face interview, technical test and questions
Cloud DevOps Engineer
Paris
€45000 - €55000
+ Data & Technology
PermanentParis, Île-de-France
CLOUD DEVOPS ENGINEER
PARIS (75)
UP TO 55K€
Une startup innovante dans le domaine de l’assurtech recherche un Cloud DevOps Engineer pour rejoindre ses équipes et contribuer activement à son développement.
LES MISSIONS
Au sein d’une équipe tech d’une dizaine de personnes, vous serez responsable de la gestion des outils d’infrastructure.
Au quotidien, vous aurez pour mission de :
- Choisir l’infrastructure appropriée en fonction des contraintes de la plateforme IT
- Développer des pipelines robustes et fluides
- Garantir le bon déploiement des solutions en production (tests unitaires, A/B testing)
- Garantir constamment la sécurité de l’infrastructure
- Travailler sur divers projets en mode AGILE
VOTRE PROFIL
- Vous justifiez d’une expérience d’au moins 2 ans en DevOps, SRE ou sysadmin
- Excellente maîtrise du Cloud AWS, Python et Terraform
- Idéalement des connaissances sur Docker et/ou Kubernetes
- L’envie d’apprendre et de monter en compétences
POUR POSTULER
Merci de me faire part de votre CV et je vous recontacterai au plus vite.
Cloud Engineer
Paris
€50000 - €55000
+ Data & Technology
PermanentParis, Île-de-France
Cloud Engineer
Paris
Up to 55K€ + bonus
Rejoignez une entreprise novatrice et dynamique au cœur de la révolution numérique de l’assurance B2B. En tant que leader de l’Assurtech, cette société s’engage à transformer et à moderniser l’industrie de l’assurance grâce à des solutions technologiques de pointe.
Missions:
En tant que Cloud Engineer / DevOps au sein de notre équipe passionnée, vous jouerez un rôle essentiel dans la conception, la mise en œuvre et la maintenance de leur infrastructure cloud sur la plateforme Amazon AWS. Vous collaborerez étroitement avec les équipes de développement pour garantir la disponibilité, la fiabilité et les performances optimales de nos applications B2B critiques. Vos principales missions incluront :
- Concevoir, mettre en œuvre et automatiser des pipelines CI/CD pour assurer un déploiement fluide et rapide des applications.
- Surveiller proactivement l’infrastructure cloud pour détecter et résoudre les problèmes de performance, de sécurité et de mise à l’échelle.
- Collaborer avec les équipes de développement pour fournir un environnement fiable pour les tests et le déploiement.
- Gérer et optimiser les ressources cloud, en veillant à ce que les coûts restent maîtrisés.
- Participer à la veille technologique et recommander les meilleures pratiques pour l’optimisation de l’infrastructure.
Profil recherché:
- Solide expérience avec Amazon AWS, y compris EC2, S3, RDS, Lambda, etc.
- Maîtrise des pratiques DevOps et des outils tels que Docker, Kubernetes, Terraform, Jenkins, etc.
- Compréhension approfondie des principes de haute disponibilité, de sécurité et de mise à l’échelle automatique.
- Capacité à travailler en équipe et à communiquer efficacement avec des développeurs et des parties prenantes non techniques.
- Souci du détail et orientation vers la résolution de problèmes.
SENIOR DATA SCIENTIST (NLP)
London
£100000 - £120000
+ Data Science
PermanentLondon
SENIOR DATA SCIENTIST (NLP)
Up to £120,000 + Bonus
LONDON
Ready to elevate your career to new heights? Join our team of experienced Data Scientists and Data Engineers to create impactful models and work with cutting-edge technologies. We aim to become the world’s largest digital establishment providing services based on Machine Learning models.
The Role:
Your day-to-day responsibilities will include:
- Deploying Data Science projects directly to the market.
- Building Machine Learning algorithms and models using Python to develop new data products and services.
- Coding and testing new algorithms for prototype and production applications using Python libraries like TensorFlow and Keras.
- Translating data into meaningful insights using Python.
- Taking the lead in interacting with customers and stakeholders to showcase the project.
Your Skills and Experience:
- MSc or PhD level education in STEM subjects.
- Proven expertise in implementing Machine Learning and clustering techniques.
- Strong commercial experience with Python and data visualization, and proficient knowledge of Python, R, and Scala.
- Previous commercial exposure to tools such as Keras, TensorFlow, Python.
- Excellent communication skills and ability to engage with teams and colleagues.
Benefits:
- Competitive salary range of £110,000 – £120,000.
- Outstanding career progression opportunities.
- Flexible working arrangements.
How to Apply:
Register your interest by sending your CV to Luc Simpson-Kent via the Apply link on this page.
Data Product Manager
£24000 - £26400
+ Data & Technology
ContractEngland
DATA PRODUCT MANAGER – (CONTRACT)
£500-550/DAY (INSIDE IR35)
6-8 MONTHS
FLEXIBLE
THE COMPANY:
Our client, a leading organization in the financial sector, is currently seeking a skilled and experienced Data Product Manager to join their expanding team. This is an exciting opportunity to work with a specialist structure and contribute to the organization’s ongoing growth and development. As a Data Product Manager, you will play a crucial role in working with stakeholders to understand the requirements to centre the multiple data sources into one centralised platform
THE ROLE:
As the Data Product Manager, you will be responsible for working closely with stakeholders to understand the requirements for designing and implementing the platform. You will be speaking with stake holders across the business so will have to have clear communication style
YOUR SKILLS AND EXPERIENCE:
The successful Data Product Manager will have the following skills and experience:
- Strong experience collaborating with data sources.
- Strong previous experience working in fast paced companies
- Strong experience merging multiple data sources into one centralized platform
- Prior experience successfully launching new products in a B2B market
Benefits:
The successful Data Product Manager will receive between £500-550 per day for the initial 6-8 month period.
How to Apply:
Please register your interest by sending your CV to Hannah Cockings via the Apply link on this page.
Note: Due to the high volume of applications we receive, only shortlisted candidates will be contacted. Thank you for your understanding.
Industry Hub
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News & Blog
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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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