• Como Growth Analytics Engineer, tu misión será que el dato del que dependen las decisiones sea fiable: instrumentar bien desde el principio, auditar lo que ya existe y dejar la medición preparada para experimentar. • Trabajarás sobre e-commerce y producto, y con equipos que necesitan leer resultados sin dudar de los números. • Aquí no vas a trabajar solo con herramientas de terceros: tenemos plataforma propia de experimentación y un entorno de agentes con MCPs que usamos a diario para auditar y analizar. • Etiquetado de eventos en GTM para GA4 y otras herramientas de analítica. • Configuraciones avanzadas en GA4 para clientes. • Diseño de exploraciones en GA4 y de los cuadros de mando que las acompañan. • Creación de informes de resultados en Data Studio y Power BI. • Ejecución de auditoría de instrumentación para cada nuevo cliente. • Diseño y liderazgo de los planes de medición y de las taxonomías de eventos entre plataformas (web, app, servidor)

• Join our Data Science and Engineering team to help make smarter choices • Analyze large amounts of platform and business data to create insights • Design and build data models using DBT and medallion architecture • Define success metrics for products and track key business metrics • Collaborate with technical and non-technical teams to collect requirements • Lead data modeling projects and choose the right tools • Work with large datasets for data-based decisions • Guide teams by creating analytical metrics and explaining data impacts • Improve processes by creating well-documented solutions • Use modern tools to enhance data architecture as it grows

• Design and build models that turn raw data into useful metrics and data products, using DBT and medallion architecture • Define what success looks like for our products, setting up and tracking key business metrics • Work with technical and non-technical teams to collect requirements, share methods, and teach best practices for using data • Lead data modeling projects, choosing the right tools and planning how to complete the work • Work efficiently with data of all sizes, including petabyte-scale datasets, to help everyone make data-based decisions • Guide partner teams by creating and explaining analytical metrics, helping them understand how data impacts different parts of the product and business • Improve our team's processes and code by creating well-documented solutions that can be used again in the future • Use modern tools (GCP BigQuery, AWS S3, Fivetran, Hightouch, and AI tools like Claude Code) and help us improve our data architecture as it grows • Collaborate with a worldwide, remote team that values learning, open source software, and new ideas

Help shape how intelligent technology delivers real outcomes across the business. In this role, you will turn challenging problems into secure, scalable applications powered by artificial intelligence and advanced analytics. You will work alongside experts across product, data, engineering, and governance to deliver solutions that matter. If you enjoy moving from concept to production and seeing measurable impact, you will thrive here. Join us as we build the next generation of intelligent capabilities. As an AI Applications Developer in the AI Solutions Team, you will design, build, and deliver intelligent applications that transform business needs into measurable outcomes. You will partner with cross-functional teams to integrate modern model-driven capabilities into our platforms, from discovery through production. You will help ensure our solutions are secure, scalable, and aligned to responsible and compliant use. You will continuously learn and apply emerging approaches to improve quality, speed, and impact. Job responsibilities - Design and deliver production-grade applications powered by large language models and advanced analytics - Build agent-based systems that plan, decompose, and execute complex workflows across tools and services - Develop and optimize prompts, evaluation methods, and guardrails to improve reliability and user outcomes - Implement retrieval-augmented generation patterns to ground model responses in trusted data sources - Integrate applications with cloud services, data stores, and APIs to support end-to-end workflows - Partner with product, data, engineering, and governance teams to define requirements and deliver solutions - Apply secure-by-design practices, including access controls, data protection, and auditability throughout development - Create automated tests, monitoring, and observability to improve quality, safety, and operability in production - Document architectures, decisions, and runbooks to enable supportability and reuse across teams - Troubleshoot performance, latency, and model quality issues and deliver iterative improvements - Stay current on advances in generative and agent-based approaches and translate them into practical solutions - Required qualifications, capabilities, and skills - Professional experience building and deploying modern applications in a production environment - Hands-on Python development experience, including writing maintainable, testable code - Demonstrated experience building intelligent applications using large language models, including prompt design and systematic evaluation - Demonstrated experience implementing agent frameworks (for example, Google Agent Development Kit or similar) - Demonstrated experience with retrieval-augmented generation solutions (indexing, retrieval strategies, grounding, and citations) - Hands-on experience with containerized development and deployment (for example, Docker and orchestration platforms) - Hands-on experience with Amazon Web Services core services for data and application workloads (for example, managed compute, storage, databases, and serverless) - Strong understanding of secure development practices, including identity and access controls and data handling principles - Ability to translate ambiguous business problems into technical designs, milestones, and measurable outcomes - Strong analytical and problem-solving skills, including root-cause analysis in production systems Preferred qualifications, capabilities, and skills - Experience deploying and operating solutions on Kubernetes (for example, Amazon Elastic Kubernetes Service) - Experience with Amazon Bedrock or similar managed model platforms and orchestration patterns - Experience building data pipelines and analytics workflows (for example, AWS Glue and Amazon Athena) - Experience with relational database design and performance tuning (for example, Amazon Relational Database Service) - Experience implementing model fine-tuning or adaptation techniques with clear evaluation and governance - Experience partnering with risk, controls, privacy, and compliance teams on model-enabled products - Experience mentoring engineers and establishing team development standards and reusable patterns About Us JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About the Team Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction. The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.