Advanced Analytics Technical Staff

What are we looking for?

• Higher Vocational Training, University Degree, or Master's related to Data Science, Artificial Intelligence, Computer Engineering, Mathematics, Statistics, Physics, or other equivalent STEM degrees.
• Knowledge of programming, data analysis, and Machine Learning.
• Knowledge of the model development lifecycle, especially its production deployment, monitoring, and evolution.
• Knowledge of or interest in MLOps technologies and practices, such as version control, APIs, containers, CI/CD, and automation.
• Ability to analyze information, interpret metrics, solve technical problems, and document the work performed.
• Interest in learning to build robust, scalable, reproducible, and maintainable AI solutions.

Previous experience is not an essential requirement. We will value any academic, professional, or personal experience related to Machine Learning, programming, APIs, containers, CI/CD, monitoring, automation, or the deployment of AI models and solutions.

At Tracasa, we are looking to incorporate an Advanced Analytics technical profile into the Innovation and Digital Advancement area.

We are looking for a person with training related to the technological field and an interest in working on advanced analytics, data science, and artificial intelligence projects to obtain knowledge from data.

What will you be working on?

You will participate in advanced analytics, Machine Learning, and Artificial Intelligence projects, with a special focus on the industrialization, production deployment, and operation of AI models and solutions.

You will work throughout the entire lifecycle of the solutions, from data preparation and model development to their packaging, deployment, monitoring, and continuous improvement in production environments.

Your main tasks will include:

• Participate in the development, training, validation, and production deployment of Machine Learning models and AI solutions.
• Prepare and transform datasets, performing cleaning, enrichment, and quality validation tasks.
• Work on the packaging and deployment of AI models and services in different environments.
• Participate in the automation of training, validation, and deployment pipelines, applying MLOps and CI/CD practices.
• Work on the monitoring of models and services, instrumenting metrics, logs, and alerts to analyze their behavior in production.
• Participate in processes of versioning, retraining, and continuous improvement of models, including the tracking of their performance and possible drifts.
• Collaborate on aspects related to the scalability, availability, and performance of the deployed solutions.

• Temporary contract, with the possibility of moving to a permanent contract if production requirements exist.