Data Scientist - (Machine Learning & Databricks)
Salary | $2,000 USD/month (Bi-weekly payments)
Location | Remote from Latin America
Schedule | Full-time
Employment Type | Contractor
Perks & Time Off | U.S. holidays off, generous PTO, internal training, and mentorship

About the Client

Latino Legends is partnering with a high-growth U.S. marketing intelligence company to find top-tier nearshore talent. Our client does not just report on data—they build with it, driving marketing decisions for over 1,000 dealer clients across digital and direct channels. They operate on a cloud-native Databricks Lakehouse platform and foster an AI-forward culture where modern tooling accelerates analysis and deployment.

The Role

As a Data Scientist, you will work primarily inside Databricks building datasets, features, and machine learning models that power marketing intelligence. You will spend your time on data preparation, exploratory analysis, feature engineering, and model training/evaluation, supported by senior engineers and architects on the production side.

Key Responsibilities





Data & Modeling (80%)
- Build and maintain data pipelines and transformations in Databricks using Python, PySpark, and SQL.
- Perform exploratory data analysis to understand marketing, campaign, and customer datasets.
- Engineer features, prepare training datasets, and train, evaluate, and tune machine learning models.
- Support model deployment and monitoring in production alongside senior engineers.
- Investigate and resolve data quality issues in source feeds and pipelines.
- Leverage AI coding tools efficiently while maintaining code quality and deep understanding.

Collaboration & Quality (20%)
- Participate in sprint planning, standups, and retrospectives within an Agile/SCRUM framework.
- Write tests, data validation checks, and participate in code reviews.
- Document datasets, features, model assumptions, and results.
- Present findings and recommendations to both technical and business s

📌 Data Scientist (México)
🏢 Latino Legends
📍 México