
Software Engineer, Behavioral Economics
- Ciudad de México
- Permanente
- Tiempo completo
- Bachelor’s degree in Computer Science, Data Engineering, Data Science, Management Information Systems, or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages (e.g., C/C++, Java, Python, R) and database languages (e.g., SQL).
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- Experience in developing and scaling data pipelines for data ETL (Extraction, Transformation, Load), machine learning models, or other data products.
- Experience with Business Intelligence tools (e.g., Tableau, Looker), AI agents, or cloud platforms..
- Master's degree or PhD in Computer Science or related technical field.
- Experience in quantitative analytics including data engineering, data analysis, machine learning, or model deployment.
- Experience managing sensitive user data, including company compliance (e.g., product log policies).
- Ability to balance tests, business logic, data quality, and infrastructure problems within an agile team.
- Ability to develop, manage, and maintain data science infrastructure and tools, ensuring reliability and performance.
- Ability to design automated solutions to process large quantities of unstructured data (product logs, panel data, large text corpuses, etc.).
- Collaborate with data scientists, researchers, and engineers to design, prototype, productionize, deploy, and monitor data products (e.g., metrics, dashboards, pipelines, models, reports, etc.) and help technical and non-technical partners understand and interpret data products.
- Implement data anonymization policies that comply with user privacy requirements.
- Explore new data sources and develop solutions for data integration, sanitization, and storage.
- Manage and optimize the team's data infrastructure (tooling, monitoring, security, reliability, performance) and proactively identify and resolve performance bottlenecks and data quality issues.
- Develop and deploy machine learning models to solve business problems, leveraging programming skills and an understanding of statistical and machine learning techniques.