Data Scientist - Production Machine Learning

Data Scientist - Production Machine Learning

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.

Qualifications

• 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 Sage Maker 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.

Additional Information

• Required Tools & Platforms
• Python
• Advanced SQL
• Git or comparable version control
• AWS Sage Maker, 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