• Collaborate with operational stakeholders (Product, Engineering, Clinical, and Engagement) to clarify analytic needs and define requirements. • Build clear analyses, visuals, and dashboards using datasets such as claims, pharmacy, FHIR, Elevate, and other internal tools. • Prepare customer-facing summaries that show Tuesday Health impact, support JOC materials, and track progress toward SLAs. • Assist with data model development by creating well-documented transformations and partner with Analytics Engineering to ensure models stay accurate and aligned with reporting needs. • Monitor data quality for dashboards and reports. Flag anomalies, locate root causes, and coordinate with cross-functional teams to reduce downstream reporting issues.

Role Description Profissional de dados com perfil analítico e visão de negócio, capaz de transformar dados de CRM em insights acionáveis e aplicar técnicas de analytics e inteligência artificial para otimizar estratégias de aquisição, retenção e relacionamento com clientes. - Profissional proativo, orientado a resultados e com forte senso de ownership. - Capaz de atuar de forma estratégica e executiva na evolução do CRM orientado a dados. Qualifications - Experiência prévia como Analista de Dados / BI / CRM. - Atuação em times cross-funcionais, colaborando com múltiplas áreas. - Vivência em contextos data-driven, com decisões orientadas por métricas. - Experiência com bases de clientes, campanhas, jornadas ou produtos digitais. - Desejável experiência em B2B, B2C ou marketplaces (não obrigatório). - Conhecimento em modelagem de dados analíticos (tabelas fato e dimensão, datasets de CRM). - Experiência com ferramentas de BI (ex: Power BI, Tableau, Looker ou similares). - Familiaridade com ambientes de dados (Data Warehouse, Data Lake, pipelines). - Entendimento de métricas de CRM, marketing, vendas e lifecycle. - Boa capacidade de documentação e comunicação de análises. - Experiência sólida com SQL para extração, transformação e análise de dados. Requirements - Afinidade com o uso de IA no dia a dia para ganho de produtividade e eficiência analítica. - Experiência ou interesse em utilizar ferramentas de IA generativa para apoiar análises exploratórias, geração de insights, otimização de queries SQL e documentação. - Capacidade de identificar oportunidades de automação de rotinas analíticas e processos de dados. - Interesse em evoluir análises descritivas para abordagens mais inteligentes, como segmentações avançadas, regras de priorização e lógicas de scoring simples. Responsibilities - Conduzir análises exploratórias, diagnósticas e de performance relacionadas a CRM, ciclo de vida do cliente, engajamento, churn e retenção. - Desenvolver e manter bases analíticas consolidadas (perfil, comportamento, transações, campanhas, interações). - Criar e documentar datasets reutilizáveis para diferentes áreas (Marketing, Growth, Vendas, Produto). - Apoiar a definição e monitoramento de métricas de CRM (KPIs, OKRs e indicadores operacionais). - Realizar estudos ad hoc para responder perguntas de negócio e orientar decisões estratégicas. - Desenvolver dashboards e análises self-service, garantindo clareza e confiabilidade das informações. - Trabalhar de forma colaborativa com times de negócio e tecnologia, atuando como ponte entre dados e decisão. - Garantir qualidade, consistência e governança dos dados de CRM. - Apoiar iniciativas de segmentação, personalização e experimentação (ex: testes A/B, cohorts). Benefits - A Experian é uma empresa global de dados e tecnologia que impulsiona oportunidades para pessoas e empresas ao redor do mundo. - A Experian investe em pessoas e em novas tecnologias avançadas para liberar o poder dos dados. - Contamos com uma equipe incrível de 25.200 colaboradores em 32 países. - A cultura da Experian, centrada nas pessoas, inclusiva e orientada por propósito, é reconhecida por diversos prêmios. - A Experian também se orgulha de ser uma empregadora que promove igualdade de oportunidades e ação afirmativa.

• Use SQL, dbt, CI/CD, Github, and Google Cloud to automate data transformation pipelines that flow to our various enterprise partners. • Use Data Visualization tools (such as Tableau) to create intuitive data products, allowing our enterprise partners to better understand their business and trust their data. • Strong communicator, not afraid to contribute during meetings with stakeholders and engineering teammates, and asks clarifying questions to better understand business requirements and opportunities. • Build subject matter expertise within the insurance domain, in order to better anticipate partners’ needs. • Recommend and adopt data governance best practices to Improve data quality and controls. • Construct data validation checks and automated unit tests to catch data quality issues early, ensuring reliable downstream analytics and partner deliverables. • Collaborate with other data analysts and engineers, sharing work and cross-training others. • Ensure data quality through automated monitoring and alerting, and occasionally serving within an on-call rotation. • Maintain a positive attitude and encourage the growth and development of team members. • Make decisions as a team. Propose your ideas. Review others’ work. Shared ownership.

• Lead the creation & development of a standard library of reporting and/or analysis solutions (report, dashboard, visualization, or other) for Data Sciences and other stakeholders. • Gather requirements from a cross-functional group to a particular study question or operational activity. • Build & configure solution to meet the requirements. • Lead validation activities to prepare reporting solutions for release/usage. • Gather (as needed) and collaborate with volunteer stakeholder group to support validation activities. • Contribute to the Data Standards Governance Committee (DSGC) for the management of standard reports. • Maintain ongoing updates to standard report templates. • Support training for the Data Sciences team of new standard reports/solutions. • Deploy standard reporting solutions for use on a study-specific basis. • Create & develop ad hoc reporting and/or analysis solutions – report, dashboard, visualization, or other – as requested by study team members. • Gather requirements from study team member(s) for ad hoc solutions. • Build & configure ad hoc solutions to meet the requirements. • Support report requestor in validation activities of study-specific ad hoc solutions to prepare for release/usage. • Support long-term maintenance of study-specific solutions and contribute to investigating issues, as raised by study team members. • Identify requirements with Data Sciences leaders to measure & monitor operational and performance metrics. • Design, build, and maintain metrics governance within Data Sciences. • Work with large data sets to analyze operational & study data and deliver reporting that outline areas for process & performance improvement/optimization (inefficiencies, inaccuracies, and other issues) to Data Sciences leadership. • Participate in the strategy, management and integration of data reporting systems that impact Data Sciences, including the assessment, integration, build of vendor systems and Alimentiv technologies. • Act as a technical system subject matter expert; perform validation and testing of systems. • Help gather and determine requirements for relevant technical systems, with cross-functional groups or other Business/Process analysts. Work closely with other technical roles (Data Management, Database Programming, Statistics, Enterprise Analyses, etc.) to drive data governance and excellence. • Assess ways to further leverage existing systems to optimize internal efficiencies and processes. • Support Data Sciences contribution to a Data Warehouse, contributing to key decisions and strategy. • While evaluating new projects or requests for enhancements, help determine the project cost, timeline, goals and feasibility and then support the project through completion.