RETAIL DATA ANALYTICS TRANSFORMATION ANALYST
On-siteMontevideo, Montevideo Department, Uruguay
Job Summary
Develop and automate data processes by designing, building, and maintaining pipelines that transform manual codes into reliable, scalable solutions. Drive the evolution toward ADA/AWS by collaborating on data migration, dataset improvement, and model enhancements for key performance indicators and commercial campaigns. Contribute to advanced analytics and AI initiatives through exploratory analysis, data preparation, and the development, validation, and tracking of machine learning models and generative AI use cases. Work with business users to define requirements, integrate solutions into existing channels, and monitor adoption impact while ensuring data quality, security, and governance standards.
Required Qualifications
- University degree or advanced training in Engineering, Systems, Computer Science, Data Science, Statistics, Mathematics, Economics, or other quantitative and technological careers
- Up to four years of experience in data, analytics, automation, development, or related areas
- Willingness to learn and assume progressive autonomy
- Analytical thinking and problem-solving orientation
- Ability to understand and transform business needs
- Knowledge of statistics, data analysis, and machine learning
- Orientation to quality, documentation, and maintainability
- Initiative, curiosity, and continuous learning
- Teamwork ability and openness to feedback
- Clear communication with technical and non-technical profiles
- Progressive autonomy and responsibility for work performed
- SQL
- Python
- Data processing and transformation
- ETL / ELT
- Data modeling and data quality
- Jupyter / notebooks
- Git and version control
- Statistics and fundamentals of Machine Learning
Desired Qualifications
- Experience developing or automating data processes
- Experience integrating information from different sources
- Participation in Data Engineering, Data Science, or Advanced Analytics projects
- Development or validation of machine learning models
- Construction of datasets, indicators, or tracking solutions
- Participation in data platform migration or evolution processes
- Experience with business data or real-world problems
- Work with multidisciplinary teams
- Knowledge of Retail Banking and/or Commercial Banking
- Relevant academic or personal projects in data, AI, or automation
- Knowledge or experience in Spark / PySpark
- ADA / AWS
- R
- APIs and system integration
- Pipeline orchestration and monitoring
- Scikit-learn or other machine learning libraries
- CI/CD and testing
- Power BI, QuickSight, or other visualization tools
- Generative AI and LLMs
- Technical English for reading documentation
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