#127006 - Data Scientist - Production Machine Learning

Job description

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