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About the Company
Mindrift connects specialists with AI projects from major technology innovators. The platform brings together professionals with real-world expertise to support the development of Generative AI. Its mission is to unlock the potential of AI through collective intelligence and help shape its future responsibly.
About the Role
Mindrift is seeking a Freelance Data Science Expert (Python & SQL) - AI Trainer to contribute to projects that improve the reasoning and problem-solving capabilities of Generative AI models.
In this role, you will create and validate complex data science problems based on real-world analytical workflows. Your work will help train AI models to address specialized questions involving data processing, statistical analysis, machine learning, and business insights.
This is a fully remote freelance opportunity for candidates residing in the specified country. You can work on a part-time schedule that fits around your existing professional or academic commitments.
Key Responsibilities
* Design original computational data science problems based on real-world analytical workflows across industries such as telecommunications, finance, government, e-commerce, and healthcare.
* Develop problems that require Python programming using libraries such as pandas, NumPy, SciPy, scikit-learn, statsmodels, Matplotlib, and Seaborn.
* Create computationally intensive problems that cannot reasonably be solved manually within days or weeks.
* Develop challenges involving multi-step reasoning in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.
* Ensure problems produce deterministic and reproducible answers by avoiding stochastic elements or using fixed random seeds.
* Build problems around practical business challenges, including customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.
* Design end-to-end challenges covering the data science pipeline, from data ingestion and cleaning to exploratory data analysis, modeling, validation, and deployment considerations.
* Incorporate big data scenarios that require scalable computational approaches.
* Verify solutions using Python, standard data science libraries, and statistical methods.
* Document problem statements with clear instructions, realistic business contexts, and verified correct answers.
Required Qualifications
* Master's or PhD degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field.
* At least 5 years of hands-on data science experience with demonstrated business impact.
* Portfolio of completed projects and publications showcasing real-world problem-solving.
* Strong Python programming skills for data science, including pandas, NumPy, SciPy, scikit-learn, and statsmodels.
* Expertise in statistical analysis and machine learning, with a deep understanding of algorithms, methods, and their practical applications.
* Proficiency in SQL and database operations for data manipulation and analysis.
* Experience with Generative AI technologies, including large language models (LLMs), retrieval-augmented generation (RAG), prompt engineering, and vector databases.
* Good understanding of MLOps practices and model deployment workflows.
* Knowledge of modern frameworks such as TensorFlow, PyTorch, and LangChain.
* Advanced English proficiency (C1 level or above).
* Ability to learn new methods, switch between tasks and topics quickly, and work with complex guidelines.
* Access to a laptop, a reliable internet connection, and sufficient time to complete project work.
Work Arrangement
This is a fully remote, part-time freelance position. Candidates must currently reside in the specified country, as location may affect eligibility and rates. Applicants are required to submit their resume in English and indicate their English proficiency level.
Compensation and Benefits
* Hourly rates of up to $60, depending on skills, experience, and project requirements.
* Flexible part-time project work that can fit around primary professional or academic commitments.
* Opportunity to contribute to advanced AI projects and strengthen your professional portfolio.
* Opportunity to influence how future AI models understand and communicate within the data science field.