About the job
This opportunity is exclusive to candidates residing in Mexico. Your residency may influence eligibility and compensation rates. Please submit your resume in English and include your proficiency level.
At Mindrift, we merge innovation with opportunity. Our vision is to harness collective intelligence to ethically shape the future of artificial intelligence.
Company Overview
The Mindrift platform connects talented professionals with cutting-edge AI projects from leading technology innovators. Our goal is to unlock the capabilities of Generative AI by leveraging practical expertise from around the world.
Role Overview
With the rapid advancement of GenAI models, one of our primary objectives is to empower them to tackle specialized inquiries and exhibit complex reasoning skills. As a Data Science AI Trainer on our platform, you will have the chance to collaborate on transformative projects.
While each project presents unique challenges, typical responsibilities include:
- Crafting original computational data science problems that replicate real-world analytical workflows across diverse sectors such as telecommunications, finance, government, e-commerce, and healthcare.
- Developing problems that necessitate Python programming solutions (using libraries like pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn).
- Ensuring that problems are computationally intensive, requiring days or weeks to solve manually.
- Creating complex problems that involve intricate reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insights extraction.
- Designing deterministic problems that yield reproducible answers, avoiding stochastic elements.
- Developing challenges based on genuine business issues, including customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.
- Designing comprehensive problems that cover the entire data science pipeline, from data ingestion to cleaning, exploratory data analysis (EDA), modeling, validation, and deployment considerations.
- Incorporating big data processing scenarios that demand scalable computational solutions.
- Validating solutions using Python with established data science libraries and statistical methodologies.
- Documenting problem statements with clear business contexts and providing verified correct answers.
How to Apply
To join us, simply apply to this post, and if you meet the qualifications, you will have the opportunity to contribute to projects that align with your expertise, on a schedule that suits you. By creating training prompts and refining model responses, you will play a pivotal role in shaping the future of AI, ensuring that technology serves everyone.

