Data Scientist (Python & SQL) - Freelance AI Trainer

Role overview

This opportunity is with a platform that pairs subject-matter experts with short-term AI projects for major technology companies. The work is focused on evaluating, testing, and improving AI systems. Participation is project-based and does not create a permanent employment relationship.

What you may work on

Depending on the project, you could be asked to build original data science challenges that mirror practical analytical work across sectors such as telecom, finance, public services, e-commerce, and healthcare.

• Develop Python-based problems that require libraries such as Pandas, NumPy, SciPy, scikit-learn, Statsmodels, Matplotlib, and Seaborn.
• Make sure the tasks are complex enough that they cannot be completed manually in a reasonable amount of time, typically days or weeks.
• Design assignments that demand multi-step reasoning in cleaning data, analyzing statistics, engineering features, building predictive models, and extracting insights.
• Build reproducible tasks with deterministic outputs; avoid randomness unless fixed seeds are used to guarantee the same result every time.
• Ground the work in realistic business use cases such as customer analysis, risk evaluation, fraud detection, forecasting, optimization, and operational improvement.
• Create complete end-to-end workflows covering data ingestion, preparation, exploratory analysis, modeling, validation, and deployment considerations.
• Include large-scale data scenarios that need efficient and scalable processing methods.
• Check solutions using Python along with standard data science packages and statistical techniques.
• Write clear task instructions with realistic business context and supply verified correct answers.

Candidate profile

This role suits experienced data science professionals who are comfortable with Python and are available for part-time, non-permanent project work.

• At least 5 years of practical data science experience with evidence of real business results.
• A strong portfolio of completed projects and publications that demonstrate applied problem-solving.
• Advanced Python skills for data science, including pandas, numpy, scipy, scikit-learn, and statsmodels.
• Deep knowledge of statistics and machine learning, including the theory behind common algorithms and how to apply them effectively.
• Strong SQL skills and experience working with databases for data handling and analysis.
• Exposure to GenAI tools such as large language models, retrieval-augmented generation, prompt engineering, and vector databases.
• Familiarity with MLOps concepts and model deployment processes.
• Working knowledge of current frameworks such as TensorFlow, PyTorch, and LangChain.
• Excellent written English at C1 level or above.

How the process works

The workflow is: apply, complete the qualification steps, join a project, finish assigned tasks, and receive payment.

Time commitment

During active phases, the expected workload is about 10 to 20 hours per week. This is only an estimate and depends on project needs; it is not a fixed or guaranteed schedule.

Compensation

Pay can reach the equivalent of $58 per hour on this project, with the exact amount depending on your experience and the speed at which you contribute. Compensation differs from project to project based on scope, complexity, and required expertise.

Application note

Please send your CV in English and clearly state your English proficiency level.