#127006 - DATA SCIENTIST - PRODUCTION MACHINE LEARNING

Liftedanupworkcompany

Contractjunior

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