About the job
This position is exclusively for candidates currently residing in South Korea. Your location may influence eligibility and rates. Please submit your resume in English, along with your English proficiency level.
At Mindrift, we merge innovation with opportunity, harnessing the power of collective intelligence to ethically shape the future of AI.
What We Do
The Mindrift platform connects talented specialists with AI projects from leading technology innovators. Our mission is to unlock the potential of Generative AI by leveraging real-world expertise from across the globe.
About the Role
As a Data Science AI Trainer, you will have the exciting opportunity to collaborate on innovative projects aimed at enhancing GenAI models, making them capable of addressing specialized inquiries and demonstrating advanced reasoning skills. You will typically engage in tasks such as:
- Designing unique computational data science problems that reflect genuine analytical workflows across various sectors, including telecom, finance, government, e-commerce, and healthcare.
- Creating challenges that necessitate Python programming for solutions, utilizing libraries such as pandas, numpy, scipy, sklearn, statsmodels, matplotlib, and seaborn.
- Ensuring that problems are computationally demanding and cannot be resolved manually within a reasonable timeframe (days/weeks).
- Developing problems that require complex reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.
- Formulating deterministic problems that yield reproducible answers, avoiding stochastic elements, or requiring fixed random seeds for exact reproducibility.
- Grounding problems in real business challenges involving customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.
- Designing comprehensive problems that cover the entire data science pipeline (data ingestion → cleaning → exploratory data analysis → modeling → validation → deployment considerations).
- Incorporating big data processing scenarios necessitating scalable computational approaches.
- Validating solutions using Python with standard data science libraries and statistical methods.
- Clearly documenting problem statements with realistic business contexts and providing verified correct answers.
Compensation
Contributors can earn up to $55 per hour, contingent on their level of expertise and contribution pace. Compensation may vary across projects based on scope, complexity, and required expertise. It is important to note that other projects on the platform might offer different earning levels based on their specific requirements.
How to Get Started
To apply, please submit your application through our platform.

