• Develop and maintain scalable data pipelines for diverse client datasets • Collaborate cross-functionally to translate complex problems into data-driven solutions • Design, implement, and optimize machine learning models for product integration • Rapidly prototype and iterate on novel analytics approaches with a focus on real-world impact • Participate in the end-to-end product development lifecycle, from conception through integration

• CDP Ownership: Take charge of the CDP applications, ensuring they are efficient to support customer-centric strategies and objectives across our brands. • Marketing Technology Guidance and Collaboration: Provide technology guidance to the consumers of our customer data as well as brand partners. (examples: Loyalty, ESP, CRM) • Team Leadership: Lead and motivate a team focused on leveraging customer data to enhance cross brand marketing, drive initiatives aimed at improving the overall customer experience and revenue. • Data Utilization: Ensure that the right customer data is accessible and utilized effectively for targeted marketing campaigns, personalized communications, and loyalty program enhancements. • Data Management: Oversee the management and maintenance of customer data within the CDP application, ensuring accuracy, completeness, and security. • Snowflake & Cloud Expertise: Leverage advanced knowledge of Snowflake architecture and cloud technologies (Azure, AWS, GCP) to optimize data storage, migration, and integration strategies. • Vendor Relationship Management: Manage relationships with third-party vendors, ensuring alignment with business objectives and compliance standards. • Compliance & Governance: Review Statements of Work (SOW) and ensure adherence to compliance and governance frameworks. • Agile & Project Management: Apply Agile methodologies and JIRA administration skills to manage project workflows, sprint planning, and delivery timelines. • Campaign Optimization: Collaborate with marketing teams to optimize CDP campaigns, ensuring personalized and targeted communications to drive customer retention and acquisition. • Collaboration: Collaborate closely with marketing, analytics, and technology teams to align customer data strategies with broader business objectives and ensure seamless integration with marketing initiatives. • Performance Monitoring: Monitor and analyze the performance of CDP activities and customer engagement metrics, providing insights and recommendations for continuous improvement. • Technology Integration: Work closely with technology teams to integrate and optimize CDP systems, ensuring seamless functionality and alignment with business needs.

• Desenvolver e implementar soluções de Data Science e Machine Learning em ambiente GCP • Construir e orquestrar pipelines de dados e modelos utilizando Python, Jupyter Notebooks e Dataproc • Atuar no desenvolvimento de aplicações de IA Generativa, utilizando LangChain, Google ADK e Vertex AI • Trabalhar com BigQuery para análise, transformação e modelagem de dados • Gerenciar artefatos de modelos e experimentos utilizando Artifact Registry • Utilizar Google Vector Database para aplicações com embeddings e busca semântica • Versionar código e pipelines utilizando GitLab • Colaborar com times multidisciplinares em ambiente ágil • Contribuir para boas práticas de governança, qualidade e segurança de dados

• Develop automated reports, dashboards, and insights across the full credit lifecycle. • Support underwriting, risk management, portfolio monitoring, and credit performance. • Build credit risk dashboards, reports, and analytics using Python and Tableau. • Analyze the credit lifecycle (underwriting, performance, delinquency, and collections). • Develop and automate reporting pipelines and monitoring frameworks. • Translate analytics into strategies for risk, business, and client teams. • Perform deep‑dive analyses on credit behavior, defaults, and scoring models. • Present insights to clients in clear formats. • Guide clients in using dashboards and analytics for decision‑making. • Ensure data quality, accuracy, and compliance with reporting standards. • Improve existing reporting and build new analytics for better forecasting and risk assessment. • Mentor junior team members on visualization, reporting, and credit analytics. • Be a trusted advisor in client meetings, presentations, and workshops.