Insurance data
Recruitment

Insurance data Recruitment

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

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

    •  
Insurance Data Recruitment
pexels-thisisengineering-3861969 (2)-modified
Data Recruitment
Women in Data Recruitment
Black in Data Recruitment
Rockborne Graduate Data Recruitment
Insurance Recruitment
pexels-pixabay-50711-modified

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?

In the insurance industry, a risk analyst plays a critical role in safeguarding the financial stability and sustainability of insurance operations. These professionals are tasked with meticulously assessing and managing a variety of risks that insurance companies encounter. This includes financial risk, operational risk, and market risk.

 

To hire and retain the best Risk Analysts, organisations should:

  • Professional Growth Opportunities
  • Innovative Work Environment
  • Build a strong employer brand
  • Establish strategic partnerships with universities and research institutions.
  • Provide competitive salary and benefits packages

 

UK Hiring Market:

In the competitive landscape of the UK insurance industry, the demand for skilled risk analysts is on the rise. The UK's insurance sector is known for its innovative approaches to risk management and data-driven decision-making. To attract top talent in risk analysis, insurance companies in the UK should implement strategic recruitment practices and emphasize their commitment to technological advancements and advanced risk assessment methodologies.

US Hiring Market:

In the United States, there is a growing demand for risk analysts in the insurance sector. Insurance companies, insurtech firms, and startups are investing heavily in risk modeling, data analytics, and predictive analysis to enhance their underwriting processes and manage risks more effectively. To compete for top talent in risk analysis, insurance organizations in the US should offer attractive compensation packages and highlight their involvement in cutting-edge risk management initiatives.

EU Hiring Market:

The European insurance market presents varying levels of demand for risk analysts across different countries. Nations with a strong insurance presence, such as Germany, France, and Sweden, have a significant need for risk analysts proficient in insurance risk analysis and regulatory compliance. Insurance companies in these regions should focus on local talent pools and emphasize their industry expertise to attract skilled risk analysts who can navigate complex regulatory environments.

Need a risk analyst? Contact one of our Insurance data recruitment experts today!

HIRING DATA ENGINEERS?

 
Data engineers play a foundational role in managing and harnessing the immense volume of data critical to the industry's operations.
 
To hire and retain the best Data Engineers, organisations should:
 
  • Provide an innovative work environment
  • Build a strong employer brand 
  • Establish strategic partnerships with universities and research institutions
  • Provide competitive salary and benefits packages
  • Provide professional growth opportunities
 

UK Hiring Market:

In the competitive landscape of the UK insurance industry, the demand for skilled data engineers is growing rapidly. The UK's insurance sector relies heavily on data-driven processes for risk assessment, claims processing, and customer engagement. To attract top data engineering talent, insurance companies in the UK should implement strategic recruitment practices and emphasize their commitment to technological advancements and data infrastructure development.

US Hiring Market:

In the United States, there is a significant demand for data engineers in the insurance sector. Insurance companies, insurtech startups, and established tech firms are investing heavily in data engineering to manage large volumes of data, build robust data pipelines, and support advanced analytics. To compete for data engineering talent in the US, insurance organizations should offer competitive compensation packages and showcase their involvement in cutting-edge data projects.

EU Hiring Market:

The European insurance market also demonstrates a need for data engineers, particularly in countries with strong insurance industry presence like Germany, France, and Sweden. These regions require data engineers proficient in insurance data architecture, data warehousing, and regulatory compliance. Insurance companies in these areas should focus on local talent pools and emphasize their industry expertise to attract skilled data engineers who can design and maintain data infrastructure to meet stringent regulatory requirements.

Need help securing data engineer talent? Speak to one of our insurance data recruitment specialists today

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.

 

UK Hiring Market:

In the competitive landscape of the UK insurance industry, the demand for skilled credit analysts is rising. The UK's insurance sector relies on prudent financial risk assessment and underwriting to ensure profitability and financial stability. To attract top credit analyst talent, insurance companies in the UK should implement strategic recruitment practices and emphasize their commitment to financial soundness and risk management.

US Hiring Market:

In the United States, there is a growing demand for credit analysts in the insurance sector. Insurance companies, including carriers and reinsurers, are focused on effective risk assessment and pricing strategies. To compete for credit analyst talent in the US, insurance organizations should offer attractive compensation packages and highlight their involvement in dynamic financial risk management initiatives.

EU Hiring Market:

The European insurance market also requires skilled credit analysts, particularly in countries with strong insurance industry presence, such as Germany, France, and Sweden. These regions necessitate credit analysts proficient in assessing financial risks and compliance with regulatory standards. Insurance companies in these areas should focus on local talent pools and emphasize their industry expertise to attract credit analysts who can effectively evaluate financial risks and contribute to the company's financial stability and profitability.

If you're looking for a great Credit analyst, look no further. Our Insurance data recruitment specialists can help. Contact us today!

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 Ops

Paris

€50000 - €60000

+ Data Engineering

Permanent
Paris, Île-de-France

To Apply for this Job Click Here

DATA OPS – CDI

PARIS (75)

UP TO 60K€ FIXE

AWS – Python – Kubernetes – MLops

Vous êtes à la recherche d’un nouveau challenge de Data Ops dans le domaine de l’assurance ? Ne cherchez plus, voici l’opportunité de vos rêves ! Une entreprise spécialisée dans l’assurance automobile des particuliers, recherche un Data Ops dans le cadre de la création d’une nouvelle plateforme data en Europe.

LE POSTE

En tant que Data ops vous travaillerez sur le maintien des infrastructures, sur le déploiement des pipeline ci/cd et des modèles ML.

Voici vos responsabilités au quotidien :

  • Se concentrer sur le déploiement des pipelines pour garantir une haute qualité et efficacité du processus de release et également dans l’environnement de production
  • Travailler en étroite collaboration avec les Data Architect pour surveiller l’architecture cible
  • Communiquer avec les Scrum Master ou les PO pour signaler les obstacles ou les améliorations pour le
    activités requises
  • Travailler en étroite collaboration avec les data scientists pour opérationnaliser les modèles ML au sein de la Data plateforme
  • Maintenir un état d’esprit agile au quotidien
  • Participer aux rituels agiles d’équipe et de train : PI planning, Sprint planning, Rétrospectives, Daily Scrum ou stand up meetings
  • Travailler en étroite collaboration avec la Data Gouvernance pour mettre en œuvre des règles de gouvernance sur les données

VOTRE PROFIL

  • Bac+5 diplôme d’ingénieur
  • 3-5 ans d’expérience sur un poste similaire
  • Excellente maîtrise de Python, Kubernetes et un cloud public (Azure, AWS, GCP)
  • Connaissance de l’environnement Linux
  • Connaissance en MLops
  • Bilingue (français et anglais)

Ce poste n’est pas ouvert au freelance

POUR POSTULER

Merci de me faire part de votre CV et je vous recontacterai au plus vite.

To Apply for this Job Click Here

Data Engineer

Paris

€50000 - €65000

+ Data Engineering

Permanent
Paris, Île-de-France

To Apply for this Job Click Here

DATA ENGINEER
PARIS (75) / LILLE (59)
50K-65K EUR

Cloud AWS – Python – PySpark – Glue

Une nouvelle opportunité s’ouvre pour un Data Engineer dans le domaine de l’assurance. La personne rejoindra une grande équipe ayant pour projet la création d’une nouvelle plateforme Data ! Si vous recherchez un défi stimulant dans un environnement qui encourage les nouvelles idées, cette opportunité est faite pour vous.

VOTRE MISSION :

  • Collaboration avec les Data Architectes pour garantir un bon alignement sur l’architecture
  • Développement des processus d’ingestion pour la diffusion des données dans le Datalake
  • Mise en place de mécanisme pour générer les couches de données organisées
  • Implémentation d’outils MLOps pour la mise en œuvre d’algorithmes ML
  • Conception de Data Warehouse pour accélérer la génération de modèles en Etoile
  • Travail dans une équipe agile avec le train Agile Release, le Product Owner et le SCRUM Master

VOTRE PROFIL :

  • 3 à 5 ans d’expérience en tant que Data Engineer
  • Compétences solides en Cloud AWS, Python, PySpark et SQL
  • Compétences avec les services AWS Cloud Computing : Glue ; Athéna ; Redshift
  • Capacité à travailler en autonomie
  • Français et Anglais : Fluent obligatoire
  • Les outils BI tels que Power BI ou QuickSight est un plus

N’hésitez plus pour postuler !

To Apply for this Job Click Here

Pricing Lead

£40000 - £70000

+ Risk Analytics

Permanent
England

To Apply for this Job Click Here

PRICING LEAD

REMOTE

UP TO £70,000

Join a leading insurance business focusing on an interesting niche in the market! They’re portfolios have grown by 30% in the last year and are looking for someone to lead their pricing team and shape strategy!

THE ROLE

  • Develop and implement innovative pricing strategies aligned with business objectives to drive revenue growth and market competitiveness.
  • Conduct thorough market research and competitor analysis to stay ahead of industry trends, ensuring our pricing remains competitive and profitable.
  • Utilize advanced analytics tools to interpret complex data sets, providing actionable insights that inform pricing decisions and identify opportunities for improvement.
  • Collaborate cross-functionally to identify and capitalize on opportunities for profit improvement through strategic pricing adjustments.
  • Develop pricing models and conduct scenario analysis to forecast the impact of pricing changes on revenue and profitability.
  • Work closely with sales, marketing, and product teams to align pricing strategies with overall business goals and product positioning.

REQUIREMENTS:

  • Experience working in general insurance
  • Experience with radar
  • Exposure to data analytics using tools such as SQL and python

HOW TO APPLY

Please send your Cv or apply below!

To Apply for this Job Click Here

Lead Pricing Modelling Analyst

Manchester

£50000 - £70000

+ Risk Analytics

Permanent
Manchester, Greater Manchester

To Apply for this Job Click Here

LEAD PRICING MODELLING ANALYST

UP TO £70,000 + PENSION + BONUS

REMOTE

One of the top insurance companies in the UK is expanding their pricing function and hiring for a Lead Analyst in their team. This role is an excellent opportunity to get involved in the top level of analytics within the industry whilst having excellent exposure with senior management in the business.

THE COMPANY

One of the top insurance companies in the UK. There is a large collaborative pricing function within the business and some of the most experience and knowledgeable leaders within the industry to learn from. There is great responsibility from day one and as mentioned there is good exposure with senior management and general opportunities to drive change for the business.

THE ROLE

You can expect to be involved in the following day to day:

  • Drive insight into pricing strategies for products across personal lines
  • Build pricing models
  • Collaborating with other areas of the business within analytics
  • Owning and sharing your ideas at an executive level, making real change
  • Supporting junior analysts in their work for development together

SKILLS AND EXPERIENCE

  • Experience in Python, R, SAS, Emblem or Radar
  • Experience working in pricing within insurance
  • Good communication skills
  • A strong university degree in a numerate discipline

SALARY AND BENEFITS

  • Up to £70,000 base salary
  • Discretionary Bonus
  • Pension contribution

HOW TO APPLY

Please register your interest by sending your CV to Shane McWilliams via the Apply link on this page.

To Apply for this Job Click Here

Pricing Specialist

£60000 - £75000

+ Risk Analytics

Permanent
West Midlands

To Apply for this Job Click Here

Pricing Specialist

West Midlands

Hybrid

Up to £75,000

Company:

I am hiring for a leading insurance company at the forefront of the industry, committed to its valued customers. They have a huge market share across the UK. This business is looking for someone innovative to come into the team to support growth and profitability using analytics and data within their pricing team.

The Role:

  • Building pricing models, using statistical techniques and machine learning algorithms.
  • Conducting data analysis and reporting to evaluate pricing performance and identify opportunities for optimization.
  • Developing and implementing pricing strategies
  • Utilizing your strong communication skills to present complex pricing concepts and strategies
  • Optimization and testing pricing models to increase effectiveness for clients

Experience Required:

  • Experience with pricing modelling within the insurance industry.
  • Experience with Emblem, Radar, and/or Earnix
  • Experience with SQL and Python to extract, manipulate, and analyse large datasets.
  • Experience using Python to build pricing models
  • Proven experience in building pricing models using statistical techniques and machine learning algorithms.
  • Excellent communication and interpersonal skills
  • Experience working with senior stakeholders and helping to implement pricing strategy

Benefits

Up to £75,000 + competitive benefits package

HOW TO APPLY

Please register your interest by sending your CV to Sean Tunley via

To Apply for this Job Click Here

Pricing Analyst

City of London

£40000 - £45000

+ Risk Analytics

Permanent
City of London, London

To Apply for this Job Click Here

Pricing Analyst

London

Hybrid

Up to £45,000

Company:

I am hiring for a leading insurance company at the forefront of the industry across several vertices including motor, home, and Pet insurance to name a few. They’re at a strong stage of growth as they look to capture market share across the UK using data to drive the business forward.

The Role:

  • Building pricing models, using statistical techniques
  • Conducting data analysis and reporting to evaluate pricing performance and identify opportunities for optimization across different portfolios
  • Developing and implementing pricing strategies
  • Communicating and reporting to senior stakeholders on commercial impact of strategies.
  • Optimisation and testing pricing models to increase effectiveness for clients
  • Developing pricing models using Radar.

Experience Required:

  • Experience in pricing analytics within the insurance industry.
  • Experience with Radar
  • Experience developing pricing models
  • Strong experience using SQL, Python, and/or R
  • STEM degree from a top university
  • Excellent communication skills

Benefits

Up to £45,000 + competitive benefits package

HOW TO APPLY

Please register your interest by sending your CV to Sean Tunley via

To Apply for this Job Click Here

Product and Pricing Analyst

Liverpool

£35000 - £45000

+ Advance Analytics & Mrktg Insight

Permanent
Liverpool, Merseyside

To Apply for this Job Click Here

Product and Pricing Analyst

£35,000-£45,000

Liverpool (Hybrid)

The Company:

  • Join an insurance company where you will take on a pivotal role in supporting a few functions across the business and delivering on the company’s mission to deliver excellent service

The Role:

As the Product and Pricing Analyst, you will:

  • Create dashboards and reporting across business functions using Power Bi
  • Complete data analysis with large data sets using SQL and Excel
  • Offer insights and relevant pricing strategies on product offerings
  • Communicate with a range of stakeholders, presenting your findings

Your Skills:

  • Excel expert
  • Strong SQL abilities
  • Power Bi experience
  • Experience using data to derive insights
  • Excellent communication skills to deliver findings to stakeholders

The Benefits:

  • Competitive salary and benefits package

To Apply for this Job Click Here

Lead Pricing Analyst – Insurance

£50000 - £70000

+ Risk Analytics

Permanent
England

To Apply for this Job Click Here

LEAD PRICING ANALYST – INSURANCE

£70,000

REMOTE

This is an exciting opportunity for an enthusiastic analyst to join a company who really prioritise the learning and development of their employees. This role would offer the change to gain a real breadth in your work within a large insurance business who offer great flexibility between teams.

THE COMPANY

This business are a leader in the UK insurance industry and have an excellent brand presence. They’ve grown significantly in recent years and now have a number of exciting opportunities across the business. They take a collaborative approach to employee development and allow a great degree of flexibility within teams and verticals across the business.

THE ROLE

You can expect to:

  • Develop and maintain a range of pricing models across insurance products
  • Share insight with the wider team and helping to improve profitability across the business
  • Analyse large sets of customer data to drive insight and commercial performance
  • Work on new product developments and proposals as part of market insight
  • Support junior analysts in the team with mentoring and management opportunities

YOUR SKILLS AND EXPERIENCE:

  • At least 3 years prior experience in pricing analytics in the insurance industry
  • Good knowledge of programming software such as SAS, SQL, Python or R
  • Ideal to have a background in the insurance space
  • Strong communication skills and desire to learn

SALARY AND BENEFITS

  • Up to £70,000 base salary
  • Excellent shares scheme
  • Annual bonus
  • 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

Data Architect

Paris

€50000 - €65000

+ Data Engineering

Permanent
Paris, Île-de-France

To Apply for this Job Click Here

DATA ARCHITECT
PARIS (75) / LILLE (59)
65K EUR


Une nouvelle opportunité s’ouvre pour un Data Architecte dans le domaine de l’assurance. Une entreprise qui combine l’expertise des grands groupes et l’agilité d’une start-up, qui vous permettra d’innover ! Si vous recherchez un défi stimulant dans un environnement qui encourage les nouvelles idées, cette opportunité est faite pour vous.

VOTRE MISSION :

  • élaborer et Concevoir l’architecture des données en réponse aux besoins métiers
  • Collaboration pour comprendre les exigences des parties prenantes et les traduire en solutions architecturales
  • Concevoir et implémenter des modèles de données efficaces et évolutifs
  • Assurer la cohérence et l’intégrité des données à travers tout le système.
  • Fournir des recommandations pour assurer une gestion efficace des données

VOTRE PROFIL :

  • 3 ans d’expérience dans un rôle similaire
  • Compétences solides avec le Cloud AWS de préférence (ouvert aux autres)
  • Compétences en Data Modelling et Data Vizualisation
  • Anglais : Fluent obligatoire

To Apply for this Job Click Here

Data Architect (CDI)

Paris

€65000 - €80000

+ Data Engineering

Permanent
Paris, Île-de-France

To Apply for this Job Click Here

DATA ARCHITECT

PARIS (75)

UP TO 80K€ FIXE

AWS – Tableau – Pyspark – Data Modeling

Vous êtes à la recherche d’un nouveau challenge de Data Architect dans le domaine de l’assurance ? Ne cherchez plus, voici l’opportunité de vos rêves ! Une entreprise spécialisée dans l’assurance automobile des particuliers, recherche un Data Architect dans le cadre de la création d’une nouvelle plateforme data en Europe.

LE POSTE

En tant que Data Architect, vous allez définir les architectures et les normes pour la stratégie de données. Vous définirez la vision et les lignes directrices pour la livraison des produits de données.

Voici vos responsabilités au quotidien :

  • Définir l’architecture cible
  • Communiquer avec les Product Owner pour atteindre l’objectif du wagon
  • Travailler en étroite collaboration avec les data scientists pour opérationnaliser les modèles ML au sein de la plateforme de données
  • Travailler en étroite collaboration avec les data engineer et data ops pour le suivi de l’architecture cible
  • Travailler en mode agile au quotidien

VOTRE PROFIL

  • Diplôme d’ingénieur en computer engineering ou mathématiques
  • 5 ans d’expérience en architecture data
  • Connaissance des architectures de plateformes de données opérationnelles
  • Connaissance de la modélisation de données et bases de données
  • Connaissance du cloud AWS
  • Connaissance d’outils BI principalement Tableau
  • Bilingue (français et anglais)
  • Nice to have : connaissance en Machine Learning

Ce poste n’est pas ouvert aux freelance

POUR POSTULER

Merci de me faire part de votre CV et je vous recontacterai au plus vite.

To Apply for this Job Click Here

Propositions & Strategy Manager

£50000 - £65000

+ Advance Analytics & Mrktg Insight

Permanent
Scotland

To Apply for this Job Click Here

Propositions & Strategy Manager

Edinburgh – Hybrid

Up to £65,000

A leading professional services firm is seeking an experienced insurance professional to drive strategic proposition development for top-tier clients.

THE COMPANY

Voted a Top Company to Work For, with a strong emphasis on diversity and inclusion, this company offers a wealth of opportunities. They are highly esteemed and provide an unparalleled network of professionals. Currently experiencing growth due to high client demand, they have exciting projects in areas such as new product innovations, Go-To-Market planning for AI implementation, and sustainability forecasting.

THE ROLE

  • Lead multiple strategy projects including Propositions Development, Go-To-Market strategies, Product Innovation, Technology Integration, and Market Transformations
  • Support clients with market assessments, scenario analysis, and forecasting
  • Drive innovation by developing disruptive strategies
  • Engage in project work from initial pitch through to implementation and execution

YOUR SKILLS AND EXPERIENCE

  • Extensive experience in strategy development and analytics, working with C-level stakeholders
  • Strong understanding of the consulting project lifecycle
  • Proficient in data analytical skills including forecasting, simulations, cost analysis, and scenario testing
  • Experience in the insurance sector with a good knowledge of industry regulations

BENEFITS

Up to £65,000

Additional flexible benefits allowance

Matched pension contribution

Health insurance

Flexible & hybrid working with no mandated days in office

HOW TO APPLY

Please register your interest by sending your CV to Rosalind Madge via the Apply link on this page

To Apply for this Job Click Here

Radar Analyst – Insurance

£35000 - £42000

+ Risk Analytics

Permanent
England

To Apply for this Job Click Here

RADAR ANALYST – INSURANCE

£42,000

REMOTE – UNITED KINGDOM

This is an exciting opportunity to join an ambitious insurance business who own a number of brands on the market. This business are known for having a really collaborative environment and offer flexible working arrangements as part of this.

THE COMPANY

Our client is a leading insurance company in the UK who own a number of brands. This role offers a chance to work across a range of insurance products, delivering pricing changes and collaborating with a number of teams in the business.

THE ROLE

  • Deliver and implement pricing changes across insurance products using Radar
  • Work on wider ad hoc live rating adjustments and queries
  • Optimise wider change processes to enhance pricing changes
  • Work cross-functionally with multiple teams across the business to ensure data and testing is optimised

YOUR SKILLS AND EXPERIENCE:

  • At least 1 year within the insurance industry
  • Essential to have experience using Radar
  • Good knowledge of programming software such as SAS, SQL, Python or R

SALARY AND BENEFITS

  • Up to £42,000 base salary
  • Discretionary bonus scheme
  • Contributory pension scheme
  • 25 days holiday
  • Private medical care

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

Industry Hub

HARNHAM
News & Blog

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

Visit our Blogs & News portal or check out our recent posts below.

Get in touch
today

Still need AI Recruitment expertise?

If you're unsure of what you’re looking for right now, get in contact anyway – we’re always getting new clients through the door.

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.
  • Enhances the improvement of loss prevention and mitigation on the periphery.

  • Reduces costs usually by implementing short-term expense reductions.

  • Utilizes data at a leisurely pace when it comes to enhancing service experiences.

  • 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.

  • The principle that carrier and customer success are indistinguishable is fully endorsed by business and operating models.

  • 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).
  • 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.

  • 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.

  • 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.

  • 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.

  • Explorations involving interconnected, multifaceted points of engagement, encompassing ecosystems and incorporated insurance.

  • 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.

  • 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.

  • 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.

  • 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.

  • Consequently, inclusion is effortlessly integrated into virtually any transaction's point of sale through collaborative alliances and interconnected systems.

  • 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.

  • 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.

     

Find BRILLIANT DATA
CAREERS & MORE Data JOBS
THAN ANYONE ELSE
- APPLY RIGHT NOW

Harnham is one of the leading data recruitment companies in the world, and we are dedicated to helping data professionals find their ideal data job.

We're proud to have access to a global network of top employers and recruitment partners, and our team specialize in connecting data professionals to the right data and analytics career opportunities.

Whether you're looking for an entry-level data job or a senior-level analytics position with a top employer, we have the right opportunity for you. Search now to find the perfect data job to match your technical skills and industry experience.

We also provide a variety of career support services, such as resume and interview preparation, to help data professionals get the most out of their job searches. Follow us on LinkedIn for all the latest news and content: