Vie - data analyst h/f

Crédit Agricole Assurances est le 1er assureur en France et le 1er bancassureur en Europe. Le groupe propose une gamme de produits et services en épargne, retraite, santé, prévoyance et assurance des biens. Ils sont distribués par les banques du groupe Crédit Agricole en France et dans 8 pays dans le monde, par des conseillers en gestion patrimoniale et des agents généraux. Les compagnies de Crédit Agricole Assurances s'adressent aux particuliers, professionnels, agriculteurs et entreprises. À fin 2023, Crédit Agricole Assurances compte 5 800 collaborateurs et son chiffre d'affaires s'élève à 37,2 milliards d'euros (normes IFRS).

Leader de l'assurance emprunteur en France et 3ème acteur européen du domaine, ainsi que 1er en France concernant la prévoyance décès, l'assurance obsèques et la dépendance, nous développons des solutions pour couvrir les risques liés au décès, à l'arrêt de travail et à la dépendance, auprès des jeunes, des familles et des séniors, des salariés et des professionnels, via des parcours multicanaux intégrés dans les process de nos partenaires : banques de détail et sociétés de financement spécialisées en France et Europe. Ce sont près de 500 collaborateurs, basés à Paris, Lille, Dublin et Milan, qui contribuent à cette activité.

Convaincus que la Diversité est une source d'enrichissement pour tous, nous sommes engagés en faveur de l'inclusion. Nos postes sont ouverts à toutes et tous, quels que soient les handicaps ou les singularités de chacun.

CACI (Credit Agricole Creditor Insurance) is the Credit Agricole Assurances Group subsidiary specialising in creditor protection insurance (CPI).

At CACI, data drives our decision-making process. Within the company, the Data Management Team is involved in all strategic projects in order to allow the business units (like the actuarial department or the development teams) to reach their objectives. The Data Quality Management team is in charge of the management and implementation of data related business projects and processes for the whole organisation. As part of the team the VIE Data Analyst will act as an SME and actively contribute to the evolution of Business Intelligence and Analytics to enable smart, secure and reliable practices across the organisation. Working with the members of the Data Quality Management team as well as external resources, the VIE Data Analyst will identify and develop areas of improvement for the final customers as well as business teams. The role involves engagement with all business departments and understanding of operating environments and constraints. The VIE Data Analyst will be required to work as part of the team responsible for:

1. Identifying, building and delivering relevant metrics, reports and dashboards through projects
2. Being a point of contact for best data/insights practices
3. Coordinating the resources on the development of new analysis models and frameworks
4. Delivering on business use cases as the company data strategy is developed further
5. Measuring ROI/Impacts and communicating on changes made, turning the results into management information
6. Provide insights and ideas to senior management to shape services and operations
7. Continuously communicate and promote analytical and data visualisation innovation

DUTIES AND RESPONSIBILITIES

1. Business Requirement Management
• Systematically capture business requirements
• Manage business user’s expectation by reviewing the priority with the management
• Facilitate the formalisation of the requirements working in cooperation with the business departments
2. Development of Business Reports / Dashboards
• Based on the functional requirement and with the help of technical experts produce the technical specifications
• Coordinate the implementation in the organisation’s BI environment the requested process as required by the business teams. Take part in the implementation phase if needed
• Apply best practices already identified by the team and suggest optimisation when possible
• Organise and coordinate the test phase
3. Communication and promotion
• Define and organise communication channels to senior stakeholders in order to promote the team’s work
• Develop a Data User Club in order to promote data analytics and data visualisation best practices and innovation
• Liaise with the group Innovation and IT data teams in order to be involved in all initiative related to data
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