About the job
This opportunity is exclusively available to candidates currently residing in Greece. Your location may impact eligibility and compensation. Please ensure your resume is submitted in English and include your level of English proficiency.
At Mindrift, we blend innovation with opportunity. Our commitment lies in harnessing the power of collective intelligence to ethically shape the future of artificial intelligence.
About Us
The Mindrift platform serves as a bridge, connecting specialists with AI projects from leading tech innovators. Our mission is to unleash the potential of Generative AI by engaging real-world expertise from around the globe.
Role Overview
As a Data Science AI Trainer, your contributions will be pivotal in enhancing GenAI models to tackle specialized inquiries and demonstrate complex reasoning capabilities. You will have the chance to engage in various projects aimed at pushing the boundaries of AI.
Typical responsibilities may include:
- Crafting original computational data science challenges that reflect real-world analytical processes across sectors such as telecom, finance, government, e-commerce, and healthcare.
- Developing challenges that require Python programming solutions, utilizing libraries like pandas, numpy, scipy, sklearn, statsmodels, matplotlib, and seaborn.
- Ensuring tasks are computationally demanding and cannot be resolved manually within practical timeframes.
- Designing problems that necessitate sophisticated reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.
- Formulating deterministic problems with reproducible solutions, avoiding stochastic elements or adhering to fixed random seeds for consistency.
- Aligning challenges with genuine business dilemmas, including customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.
- Constructing comprehensive problems that cover the entire data science pipeline, from data ingestion to deployment considerations.
- Integrating big data processing scenarios that require scalable computational methodologies.
- Validating solutions using Python along with standard data science libraries and statistical techniques.
- Clearly documenting problem statements with realistic business contexts and providing verified accurate answers.
Getting Started
To apply, submit your application through this post, qualify, and seize the opportunity to contribute to projects that align with your expertise, on your own timetable. From crafting training prompts to refining model responses, help us shape the future of AI, ensuring its benefits are wide-reaching.

