• Design, develop, validate, deploy and evolve analytical and predictive models that deliver measurable business impact. • Structure and lead end-to-end data science initiatives. • Understand business problems and translate them into analytical hypotheses, statistical models and machine learning solutions. • Develop, train, validate and monitor predictive, classification, prescriptive and segmentation models. • Work with large volumes of structured and unstructured data. • Build analytical pipelines and participate in the industrialization/operationalization of models in production. • Define model performance metrics and monitor drift, accuracy, stability and business impact. • Perform data exploration, feature engineering, variable selection and statistical testing. • Support analytical data architecture together with Data, Engineering and BI teams. • Ensure best practices for versioning, documentation, reproducibility and model governance. • Communicate analytical results in an executive, decision-oriented manner. • Act as a technical reference for more junior analysts and data scientists. • Participate in defining the data roadmap, use cases and prioritization of AI and Analytics initiatives.

• Provide technical solutions for new features and support existing functionalities; • Build and maintain services related to the Card project, ensuring core card management functions work in the app; • Assist other team members with technical issues, always prioritizing the best solution for the business; • Develop with a focus on quality, following best practices and ensuring clean, readable code (clean code); • Act with an intrapreneurial mindset, aligning with company objectives.

• Own problems end-to-end, from discovery and ideation through to delivery and iteration • Build and ship high-quality product features using Python and TypeScript • Collaborate closely with Product and Design to shape user-centric solutions • Contribute to product decisions, bringing technical insight into trade-offs and opportunities • Write clean, maintainable, and well-tested code across the stack • Continuously improve product performance, usability, and reliability • Participate in experimentation, A/B testing, and data-driven decision making • Take responsibility for outcomes, not just output, focusing on user and business impact

• Design, develop, and maintain full stack applications using React, TypeScript, and Node.js • Build and scale microservices-based architectures to support evolving product needs • Develop and integrate APIs and GraphQL services • Work with databases such as MongoDB to manage and optimise data models • Collaborate with cross-functional teams to deliver features end-to-end • Contribute to system design, architecture decisions, and technical direction • Ensure code quality through testing, reviews, and best engineering practices • Leverage AI tooling (e.g. coding assistants, automation tools) to improve development efficiency • Optimise application performance, scalability, and reliability • Participate in the full SDLC, from planning and design through to deployment and iteration