Overview
Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.
What This Opportunity Involves
While each project involves unique tasks, contributors may:
- Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare)
- Create problems requiring Python programming to solve (using Pandas, Numpy, Scipy, Sklearn, Statsmodels, Matplotlib, Seaborn)
- Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks)
- Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction
- Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility
- Base problems on real business challenges: customer analytics,



risk assessment, fraud detection, forecasting, optimization, and operational efficiency
- Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations)
- Incorporate big data processing scenarios requiring scalable computational approaches
- Verify solutions using Python with standard data science libraries and statistical methods
- Document problem statements clearly with realistic business contexts and provide verified correct answers

What We Look For
This opportunity is a good fit for Data Science specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:
- 5+ years of hands-on data science experience with proven business impact
- Portfolio of completed projects and publications showcasing real-world problem-solving
- Expert Python

📌 Data Scientist (España)
🏢 Mindrift
📍 España