Data Scientist

Job not on LinkedIn

🔥 12 hours ago

💃 Latin America – Remote

💵 $2k / month

⏳ Contract/Temporary

🟢 Junior

📊 Data Scientist

🚫👨‍🎓 No degree required

👻 Ghost score 0%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Latino Legends

WebsiteLinkedInAll Job Openings

1 - 10 employees

Founded 2025

🎯 Recruiter

👥 HR Tech

Recruitment • HR Tech

Latino Legends is a recruitment platform and talent marketplace focused on connecting Latin American professionals with remote job opportunities worldwide. The company operates a candidate portal that offers transparent application tracking, profile management, and real-time notifications, and it supports employers by sourcing and placing Latin American talent across a range of remote roles and industries. Latino Legends emphasizes showcasing Latin American skills and helping candidates access global opportunities while managing the hiring process for employers.

📋 Description

• Build and maintain data pipelines and transformations in Databricks using Python, PySpark, and SQL • Perform exploratory data analysis on marketing, campaign, and customer datasets • Engineer features and prepare training datasets • 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 • Use AI coding tools efficiently while maintaining code quality and understanding • Participate in sprint planning, standups, and retrospectives within an Agile/SCRUM framework • Write tests and data validation checks • Participate in code reviews • Document datasets, features, model assumptions, and results • Present findings and recommendations to technical and business stakeholders

🎯 Requirements

• 1–3 years of hands-on experience in data science, machine learning, or analytics engineering, including internships, co-ops, research, or complex projects • Degree in Computer Science, Statistics, Mathematics, Engineering, Data Science, or comparable practical experience • Solid proficiency with Python, including pandas, NumPy, and scikit-learn • Solid proficiency with SQL, including joins, aggregations, and window functions • Understanding of supervised learning, train/test splits, feature engineering, cross-validation, and evaluation metrics including ROC AUC, RMSE, precision, and recall • Working knowledge of descriptive statistics, hypothesis testing, data profiling, and data cleaning • Proficiency with Git, collaborative development, and AI-assisted development tools such as Cursor, GitHub Copilot, or Claude • Strong written and spoken English skills • Databricks or PySpark experience is nice to have • Exposure to MLflow, Delta Lake, or Azure cloud services is nice to have • Experience with time-series forecasting, uplift modeling, or audience segmentation is nice to have • Familiarity with Power BI, Tableau, Plotly, or CI/CD pipelines is nice to have • Interest in Large Language Models and generative AI applications is nice to have

🏖️ Benefits

• U.S. holidays off • Generous PTO • Internal training • Mentorship • Bi-weekly payments • Hands-on experience in Databricks on a modern lakehouse platform • Career growth and code review support from senior architects • Collaborative, cross-border culture across the U.S. and Latin America