About the job
This position is exclusively for candidates currently residing in Australia. Your location may influence eligibility and remuneration. Please submit your resume in English and specify your English proficiency level.
At Mindrift, innovation converges with opportunity. We harness the power of collective intelligence to ethically shape the future of AI.
About Us
The Mindrift platform connects experts with AI projects from leading technology innovators. Our mission is to unleash the potential of Generative AI by leveraging real-world expertise globally.
Role Overview
As a Data Science Engineer, you will play a crucial role in advancing GenAI models, enhancing their capacity to address specialized inquiries and develop complex reasoning skills. Your collaboration on diverse projects will be invaluable.
Typical responsibilities may include:
- Designing innovative computational data science challenges that replicate real-world analytical workflows across various industries (telecom, finance, government, e-commerce, healthcare).
- Creating Python programming tasks that utilize libraries such as pandas, numpy, scipy, sklearn, statsmodels, matplotlib, and seaborn.
- Ensuring that the problems are computationally intensive and cannot be manually solved in a reasonable timeframe.
- Developing problems that require intricate reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.
- Creating deterministic problems with reproducible answers, avoiding stochastic elements or requiring fixed random seeds for exact reproducibility.
- Base problems on genuine business challenges, including customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.
- Designing end-to-end problems that cover the entire data science pipeline (data ingestion → cleaning → exploratory data analysis → modeling → validation → deployment considerations).
- Incorporating big data processing scenarios requiring scalable computational strategies.
- Verifying solutions using Python with standard data science libraries and statistical techniques.
- Documenting problem statements clearly within realistic business contexts and providing verified solutions.
Getting Started
To apply, simply respond to this post, meet the qualifications, and seize the opportunity to contribute to projects that align with your skills, on your own schedule. From crafting training prompts to refining model outputs, you'll help shape the future of AI while ensuring that technology serves everyone.