Data Scientist

This is a fully remote position, open to applicants in Latin America.

📋 Description

• Develop and manage data pipelines and transformations within Databricks utilizing Python, PySpark, and SQL.

• Conduct exploratory data analysis on marketing, campaign, and customer datasets.

• Create features and prepare datasets for training purposes.

• Train, assess, and optimize machine learning models.

• Assist in the deployment and monitoring of models in production alongside senior engineers.

• Investigate and address data quality issues in source feeds and pipelines.

• Efficiently utilize AI coding tools while ensuring code quality and comprehensibility.

• Engage in sprint planning, daily standups, and retrospectives within an Agile/SCRUM framework.

• Write tests and implement data validation checks.

• Take part in code review processes.

• Document datasets, features, model assumptions, and outcomes.

• Share findings and recommendations with both technical and business stakeholders.

⛳️ Requirements

• 1–3 years of practical experience in data science, machine learning, or analytics engineering, including internships, co-ops, research, or complex projects.

• A degree in Computer Science, Statistics, Mathematics, Engineering, Data Science, or equivalent practical experience.

• Strong proficiency in Python, including libraries such as pandas, NumPy, and scikit-learn.

• Solid SQL proficiency, including joins, aggregations, and window functions.

• Understanding of supervised learning, train/test splits, feature engineering, cross-validation, and evaluation metrics such as ROC AUC, RMSE, precision, and recall.

• Working knowledge of descriptive statistics, hypothesis testing, data profiling, and data cleansing.

• Proficient in Git and collaborative development, with familiarity in AI-assisted development tools like Cursor, GitHub Copilot, or Claude.

• Strong verbal and written communication skills in English.

• Experience with Databricks or PySpark is desirable.

• Exposure to MLflow, Delta Lake, or Azure cloud services is a plus.

• Familiarity with time-series forecasting, uplift modeling, or audience segmentation is advantageous.

• Knowledge of Power BI, Tableau, Plotly, or CI/CD pipelines is beneficial.

• Interest in Large Language Models and generative AI applications is a plus.

🏝️ Benefits

• U.S. holidays off.

• Generous paid time off (PTO).

• Internal training opportunities.

• Mentorship programs.

• Bi-weekly payment schedule.

• Practical experience with Databricks on a modern lakehouse platform.

• Opportunities for career advancement and code review support from senior architects.

• A collaborative, cross-border culture spanning the U.S. and Latin America.