We are seeking a Data Scientist with hands-on experience building, deploying, and maintaining production machine learning solutions in a cloud environment. This role will develop scalable ML models, improve the data pipelines that support them, and collaborate with engineering and business stakeholders to deliver data-driven solutions.

This is a contract role supporting a remote, cross-functional team. The successful candidate must have experience taking machine learning models beyond notebook-based development and supporting them in live production environments.

Enterprise experience strongly preferred.

Key Responsibilities

* Develop, deploy, and maintain machine learning models in production environments.

* Perform exploratory data analysis to identify patterns, opportunities, and modeling approaches.

* Conduct feature engineering and prepare data for machine learning workflows.

* Build and improve data pipelines supporting model development, deployment, and maintenance.

* Monitor production models and help address performance or operational issues.

* Collaborate with engineering and business stakeholders to translate business needs into scalable machine learning solutions.

* Use version-control and collaborative development practices to manage production code.

* Work independently while communicating progress, risks, and technical findings clearly.

* Contribute to LLM- or AI-agent-based capabilities where applicable.

Must-Have Skills

* At least 2 years of experience building and maintaining production machine learning models.

* Strong Python programming skills.

* Advanced SQL skills.

* Experience deploying machine learning models into production.

* Experience monitoring or maintaining models after production deployment.

* Experience with AWS SageMaker or another enterprise machine learning platform, such as Vertex AI or Azure Machine Learning.

* Experience supporting production machine learning pipelines.

* Experience with Git or another version-control system.

* Experience performing exploratory data analysis and feature engineering.

* Experience building or improving data pipelines that support machine learning workflows.

* Ability to work independently in production environments.

* Strong communication and cross-functional collaboration skills.

Nice-to-Have Skills

* Experience with MLflow, Airflow, dbt, or similar MLOps and workflow tools.

* Experience with Snowflake.

* Experience supporting marketing or growth use cases.

* Experience with experimentation or causal inference.

* Experience with large language models.

* Experience with AI agents or agentic capabilities.

* Experience working in Agile development environments.

* Experience developing scalable machine learning solutions in enterprise environments.

Required Tools & Platforms

* Python

* Advanced SQL

* Git or comparable version control

* AWS SageMaker, Vertex AI, Azure Machine Learning, or another enterprise ML platform

* Production machine learning deployment and monitoring tools

Location, Time & Engagement

* Location: Remote, LATAM

* Candidates must be located in an approved LATAM country.

* The role requires working-hour alignment with a U.S. team operating between Pacific and Eastern time zones.

* Schedule: Full-time, approximately 40 hours per week

* Engagement type: Contract

* Expected contract end date: December 31, 2026