Data Scientist (Python & SQL) - Freelance AI Trainer

Overview

Mindrift brings together subject-matter experts for project-based AI work with major technology companies. The focus is on evaluating, stress-testing, and enhancing AI systems. This is not a permanent role; participation is tied to individual projects.

Please share your CV in English and mention your English proficiency level.

What this opportunity involves

Different projects may include different tasks, but contributors can be expected to handle work such as:

• Building original, computation-heavy data science challenges that mirror practical analytical work across fields like telecom, finance, public sector, e-commerce, and healthcare.
• Writing Python-based problem sets that use tools such as Pandas, NumPy, SciPy, scikit-learn, Statsmodels, Matplotlib, and Seaborn.
• Making sure the problems are sufficiently demanding that they cannot be solved manually in a reasonable amount of time, often taking days or weeks to work through.
• Developing tasks that require multi-step reasoning in areas like data preparation, statistical testing, feature engineering, predictive modeling, and drawing insights.
• Creating deterministic exercises with reproducible outcomes by avoiding randomness or by using fixed random seeds where needed.
• Grounding scenarios in genuine business use cases such as customer analytics, risk evaluation, fraud detection, forecasting, optimization, and operational improvement.
• Designing full-lifecycle data science tasks covering ingestion, cleaning, exploratory analysis, modeling, validation, and deployment considerations.
• Including large-scale data processing situations that call for efficient and scalable methods.
• Checking solutions with Python, standard data science libraries, and statistical techniques.
• Writing clear problem statements with realistic business settings and supplying validated correct answers.

What the client is looking for

This is best suited to data science professionals with Python experience who are open to part-time, non-permanent project work. Ideal contributors should bring:

• At least 5 years of practical data science experience with measurable business outcomes.
• A portfolio of finished projects and published work demonstrating applied problem-solving.
• Advanced Python skills for data science, including pandas, numpy, scipy, scikit-learn, and statsmodels.
• Strong capability in statistical analysis and machine learning, with a deep understanding of methods, algorithms, and where they apply in practice.
• Advanced SQL skills and experience with database operations for analysis and data manipulation.
• Exposure to GenAI tools such as LLMs, RAG, prompt engineering, and vector databases.
• Familiarity with MLOps practices and deployment workflows for models.
• Knowledge of current frameworks such as TensorFlow, PyTorch, and LangChain.
• Excellent written English at C1 level or higher.

How the project works

The process follows a simple path: apply, complete qualification steps, join a project, finish assigned tasks, and receive payment.

Time commitment

During active phases, the expected workload is approximately 10 to 20 hours per week. This is only an estimate and is not guaranteed; it applies solely while a project is active.

Compensation

Contributors may earn up to the equivalent of 55 USD per hour on this project, depending on expertise and pace. Pay can differ across projects based on scope, complexity, and the level of skill required.

Additional information

This opportunity is project-based rather than a permanent job. Compensation and workload may vary from one project to another.