Uncover

• Execute the integration of marketing, media and business data sources into the Uncover platform, ensuring connection stability, continuous updates and clear communication with clients regarding requests and deliverables. • Apply established standards for data processing, organization and governance to ensure integrity, traceability, security and consistency of ingested data. • Design and perform validation processes for the data used in measurement models, ensuring reliability, historical consistency and adherence to analytical assumptions during setup and ongoing runs. • Monitor ingestion and update routines for data sets, identifying inconsistencies, technical failures or operational risks and engaging the responsible teams when necessary. • Keep documentation in Notion up to date regarding processes, ingestion assumptions, transformations, validations and operational standards, ensuring alignment across teams. • Organize and prioritize client requests according to guidance from the Squad Lead (Account Management), ensuring deadlines are met, technical quality is maintained and operations run smoothly. • Build and maintain structured client relationships by leading technical alignments, clarifying questions, tracking deliveries, proposing creative innovations and ensuring satisfaction through disciplined, operation-focused excellence. • Provide guidance and training to clients on platform usage, data structure, measurement assumptions and best practices to promote autonomy and maximize product value.

• Implementation of production ML infrastructure: Design, implement, and maintain machine learning pipelines and systems in production environments, ensuring scalability, reliability, monitoring, and integration with the platform architecture • Development and evolution of product-focused models: Develop, train, validate, and optimize ML models with an emphasis on direct impact to product features and value generation for customers • MLOps and model governance: Establish practices for model versioning, deployment, monitoring, auditing, and traceability, ensuring reproducibility, security, and compliance across the solution lifecycle • Monitoring and performance of ML systems: Track performance, accuracy, drift, and model stability metrics in production, proposing continuous adjustments to ensure operational efficiency and sustainability • Integration with engineering architecture: Collaborate with Software Engineering and Data Engineering to ensure ML systems align with architectural standards, coding best practices, and scalability requirements • Code quality and sustainability: Produce clean, testable, and efficient code, considering time complexity, computational cost, and long-term maintainability, following mature engineering standards • Applied research and product-driven innovation: Explore new techniques, frameworks, and ML approaches with a focus on practical applicability and concrete improvements to product and infrastructure • Cross-functional collaboration and technical support: Act as a technical ML reference within Engineering, supporting Product and other areas in understanding intelligent systems and ensuring alignment between strategy and technical execution

• Execute integration of marketing, media and business data sources (sales, revenue, campaign calendar) into the Uncover platform, ensuring connectivity, continuous updates and clear communication with the client regarding requests and deliverables. • Apply established standards for data handling, organization and governance to ensure integrity, traceability, security and consistency of ingested data. • Design and execute validation processes for the data used in measurement models, ensuring reliability, historical consistency and adherence to analytical assumptions during setup and recurring cycles. • Monitor ingestion and data update routines, identify nonconformities, technical failures or operational risks, and engage the responsible teams when necessary. • Keep documentation in Notion up to date on processes, ingestion assumptions, transformations, validations and operational standards, ensuring alignment across teams. • Organize and prioritize client requests according to guidance from the Squad Lead (Account Management), ensuring deadlines are met, technical quality and smooth operations. • Build and maintain structured client relationships by conducting technical alignments, answering questions, tracking deliveries, proposing creative innovations and ensuring client satisfaction with disciplined focus on operational excellence. • Provide guidance and training to clients on platform usage, data structure, measurement assumptions and best practices, promoting autonomy and better product utilization.

• Ensure system reliability and quality: Develop and maintain high-quality code, prioritizing availability, security, data integrity, and prevention of recurring incidents. • Deliver value consistently: Build complete, tested features aligned with the product's real needs, balancing speed and technical robustness. • Make well-founded technical decisions: Evaluate trade-offs considering performance, maintainability, security, cost, and business impact, avoiding over-engineering. • Collaborate and unblock the team: Work collaboratively in code reviews, pair programming, and technical discussions, taking collective responsibility for the squad's results. • Co-create solutions with Product and Data: Contribute technically to scope definition, assessing feasibility, risks, and alternatives before development begins. • Contribute to architectural evolution: Identify technical debt, bottlenecks, and opportunities for structural improvement, actively participating in architecture evolution. • Adopt an AI-first mindset: Use AI tools to improve productivity and quality while retaining technical responsibility for decisions and architecture. • Communicate clearly and responsibly: Maintain transparency about deliveries, risks, and blockers, document relevant decisions, and ensure stakeholder alignment.

• Technical diagnosis during the sales process: Participate in strategic meetings led by the Sales Account Executive, deepening technical understanding of the client's data, media, integrations, and analytical maturity. • Solution feasibility analysis: Assess the client's technical capabilities (data, tools, integrations) and ensure the proposed scope is feasible and sustainable. • Technical scoping: Translate business needs into clear technical requirements, supporting the development of the commercial proposal. • Technical application of Synapse: Support the AE in the technical application of Synapse, ensuring consistency between diagnosis, solution, and expected impact. • Integration with Operations and Data teams: Serve as a bridge between Sales and Operations, anticipating risks and ensuring expectations are aligned prior to closing. • Technical support in complex negotiations: Take part in discussions with the client's technical teams, addressing questions about architecture, data, and methodology. • Documentation and delivery handoff: Ensure all technical assumptions are documented to facilitate a structured handoff to Operations and Customer Experience. • Structured feedback to Product and Operations: Share recurring technical insights identified in the market to improve the platform and internal processes.

• Execute integration of marketing, media and business data sources (sales, revenue, promotional calendar) into the Uncover platform, ensuring connectivity, continuous updates and clear communication with the client regarding requests and deliverables. • Apply established standards for data processing, organization and governance to ensure integrity, traceability, security and consistency of ingested data. • Design and execute validation processes for the data used in measurement models, ensuring reliability, historical coherence and adherence to analytical assumptions in setup and recurring processes. • Monitor ingestion and update routines for data sets, identifying nonconformities, technical failures or operational risks and engaging responsible teams when necessary. • Keep Notion documentation up to date on processes, ingestion assumptions, transformations, validations and operational standards, ensuring alignment across teams. • Organize and prioritize client requests according to guidance from the Squad Lead (Account Management), ensuring deadlines are met, technical quality and operational fluidity. • Build and maintain structured client relationships by conducting technical alignments, clarifying doubts, tracking deliveries, suggesting innovations creatively and ensuring satisfaction through disciplined focus on operational excellence. • Provide guidance and training to clients on platform usage, data structure, measurement assumptions and best practices, promoting autonomy and better product adoption.

• Development of statistical and machine learning models: design, validate, and evolve statistical models and algorithms applied to marketing intelligence, ensuring methodological robustness, technical consistency, and alignment with the product's strategic needs. • Productization and scalability of analytical solutions: turn analytical models into scalable, product-integrated solutions that ensure operational efficiency, reproducibility, and reduced manual dependency. • Technical structuring of studies and hypotheses: define methodological approaches, statistical criteria, and modeling strategies based on business problems and squad priorities. • Implementation and production monitoring: oversee model deployment in production environments, monitoring performance, degradation, stability, and the need for continuous recalibration. • Collaboration with multidisciplinary squads: work together with Engineering, Product, Martech, and Insights to translate technical and business needs into viable, strategic analytical solutions. • Exploratory analysis and data validation: carry out in-depth exploratory analyses, assess data quality and consistency, and propose structural adjustments when necessary. • Technical documentation and methodological governance: ensure clear documentation of assumptions, code, methodological decisions, and statistical rationale, promoting standardization and continuity of technical knowledge. • Applied research and technical advancement: investigate new methodologies, statistical techniques, and machine learning approaches that can raise Uncover’s analytical maturity and competitive differentiation.

• Definir e evoluir a arquitetura de Machine Learning e aplicações com IA generativa (LLMs, agentes, RAG), estabelecendo direções técnicas de longo prazo com foco em escalabilidade, confiabilidade e impacto no produto. • Estabelecer padrões de excelência para modelagem, versionamento, validação e monitoramento, além de diretrizes para uso de IA generativa (qualidade, custo, observabilidade, segurança e uso responsável). • Guiar a evolução de MLOps, garantindo pipelines robustos, deploy contínuo, monitoramento e governança de modelos e sistemas de IA em produção. • Identificar e liderar iniciativas estratégicas de ML e IA generativa, direcionando aplicações de alto impacto no produto e no negócio. • Atuar nos problemas mais críticos da companhia, definindo soluções e trade-offs de longo prazo que equilibrem escala, custo e complexidade. • Influenciar decisões técnicas entre times de Engenharia, Dados e Produto, garantindo consistência arquitetural e visão de longo prazo. • Elevar o nível da equipe por meio de mentoria, revisão de soluções e disseminação de boas práticas, fortalecendo a maturidade da disciplina.

• Work together with Sales, Marketing, Product, Engineering and Operations teams, providing analytical support and guiding data-driven decisions across each area. • Orchestrate the end-to-end development of analytical solutions, from ideation through to final execution. • Translate analytical results into actionable recommendations, contributing to the planning and prioritization of projects, products and business initiatives. • Develop and implement marketing science algorithms. • Ensure data quality by correcting inconsistencies, validating information, and transforming data to facilitate analysis and insight generation.