About the job
This opportunity is exclusive to candidates currently residing in Argentina. Your location may impact eligibility and compensation. Please submit your resume in English and specify your level of English proficiency.
At Mindrift, we merge innovation with opportunity. We leverage collective intelligence to ethically shape the future of AI.
About Us
The Mindrift platform bridges specialists with AI projects from leading tech innovators. Our mission is to harness the potential of Generative AI by utilizing real-world expertise from around the globe.
Position Overview
As a Data Science AI Trainer on our platform, you will contribute to enhancing GenAI models that are rapidly evolving to tackle specialized queries and complex reasoning tasks. Your collaboration in our projects will be invaluable.
In this role, you will typically:
- Create unique computational data science challenges that emulate real-world analytical workflows across various sectors such as telecom, finance, government, e-commerce, and healthcare.
- Develop questions that necessitate Python programming solutions, employing libraries like pandas, numpy, scipy, sklearn, statsmodels, matplotlib, and seaborn.
- Ensure that the problems are computationally intensive and cannot be resolved manually in a reasonable timeframe (days/weeks).
- Formulate challenges that require intricate reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.
- Design deterministic problems with reproducible outcomes, avoiding stochastic elements and employing fixed random seeds for exact replication.
- Base your challenges on genuine business issues such as customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.
- Create comprehensive problems that encompass the entire data science pipeline—from data ingestion to cleaning, exploratory data analysis, modeling, validation, and deployment considerations.
- Incorporate scenarios involving big data processing that require scalable computational methods.
- Validate solutions through Python, applying standard data science libraries and statistical techniques.
- Clearly document problem statements with realistic business contexts and provide confirmed correct answers.
Application Process
To get started, simply apply to this post, qualify, and seize the chance to work on projects in line with your expertise, at your convenience. By creating training prompts and fine-tuning model responses, you will play a role in shaping the future of AI, ensuring technology serves everyone.