• In this role, you will build data products, troubleshoot tracking issues, and conduct deep dive analyses that unlock actionable insights for the business. • Responsibilities include: Utilizing data analytics and visualization tools to provide statistical insight for the business – these tools include but are not limited to Adobe Customer Journey Analytics, Azure Databricks, SQL, and Power BI • Owning key business datasets and providing recommendations for action • Identifying tracking gaps and partnering with developers and business teams to resolve them • Discovering opportunities to enhance data collection and instrumentation • Integrating external data sources to enrich digital analytics • Delivering recurring reports and supporting ad hoc analysis needs. • Be able to turn around projects in a tight timeline. • Leading end-to-end analytical projects with long-term impact • Staying current with emerging digital analytics tools and methodologies, and advocating for continuous improvement

• Desenvolvimento e Implementação: Criar e manter soluções robustas de IA, Machine Learning e IA Generativa, com foco em Processamento de Linguagem Natural (PLN) e Large Language Models (LLMs). • Gestão de Dados: Realizar a análise, tratamento, limpeza e preparação de grandes volumes de dados estruturados e não estruturados para treinamento de modelos. • Engenharia de Pipelines: Desenvolver, otimizar e sustentar pipelines de dados e fluxos de inferência para garantir a performance das soluções em produção. • Integração Sistêmica: Apoiar tecnicamente a integração de módulos de IA com os sistemas corporativos e plataformas de hardware do Instituto. • Qualidade e Monitoramento: Executar testes rigorosos, validações de acurácia e monitoramento contínuo de desempenho através de práticas de MLOps. • Pesquisa e Inovação: Investigar e aplicar novas tecnologias, algoritmos e frameworks para a melhoria contínua dos produtos e processos internos. • Governança e Ética: Garantir que todos os modelos desenvolvidos estejam em conformidade com os requisitos éticos e as diretrizes da Lei Geral de Proteção de Dados (LGPD). • Documentação e Colaboração: Elaborar documentação técnica detalhada e colaborar ativamente com equipes multidisciplinares de engenharia e pesquisa.

• Research, evaluate, and integrate cutting-edge AI APIs and tools (LLMs, generative AI, computer vision, etc.) to solve business problems in a creative and pragmatic way. • Explore and apply modern techniques such as prompt engineering, RAG (Retrieval-Augmented Generation), and model fine-tuning to create innovative solutions. • Rapidly develop functional prototypes to validate hypotheses, using third-party tools or building custom components. • Lead the technical evaluation of AI solutions from partners and vendors, helping determine the fastest route to value. • When the decision is to “Build,” transform prototypes into robust, scalable, and secure solutions using software engineering and MLOps best practices. • Work in a paired model with the Cell Lead, actively participating in discovery cycles and providing the technical feasibility perspective from the outset.

• Identify and prioritize exposure risk across endpoints and identity systems. • Convert endpoint/identity signals into exploitability-aware exposure intelligence. • Produce clear remediation plans; support validation and closure tracking. • Partner with IAM/endpoint teams to implement durable corrective actions.