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, testing, and refining AI systems. This is not a permanent role; participation is assignment-based and tied to individual projects.

Please provide your CV in English and include your English proficiency level.

What you may work on

• Building original data science challenges that reflect real analytical work across sectors such as telecom, finance, public services, e-commerce, and healthcare
• Writing Python-based problems that use tools like Pandas, NumPy, SciPy, scikit-learn, Statsmodels, Matplotlib, and Seaborn
• Making sure tasks are computationally heavy enough that they cannot be completed manually in a practical timeframe of days or weeks
• Creating tasks that require multi-step reasoning in data preparation, statistical analysis, feature engineering, predictive modelling, and insight generation
• Designing reproducible problems with deterministic outputs, avoiding randomness unless a fixed seed is used
• Grounding scenarios in realistic business needs such as customer analytics, risk evaluation, fraud detection, forecasting, optimisation, and operational efficiency
• Developing end-to-end assignments that cover the full data science workflow, from data ingestion and cleaning through EDA, modelling, validation, and deployment considerations
• Including large-scale data processing use cases that demand efficient and scalable methods
• Checking solutions with Python, standard data science libraries, and statistical techniques
• Writing clear task instructions with believable business context and validated correct answers

Candidate profile

This opportunity suits experienced data science professionals who are comfortable with Python and open to part-time, project-based work.

• At least 5 years of hands-on data science experience with measurable business outcomes
• A portfolio of completed work and publications that demonstrate practical problem-solving
• Advanced Python skills for data science, including pandas, numpy, scipy, scikit-learn, and statsmodels
• Strong command of statistical analysis and machine learning, including both theory and real-world application
• Advanced SQL and database handling skills for data manipulation and analysis
• Exposure to GenAI tools and workflows, such as LLMs, RAG, prompt design, and vector databases
• Familiarity with MLOps and model deployment processes
• Knowledge of contemporary frameworks including TensorFlow, PyTorch, and LangChain
• Excellent written English at C1 level or above

Process

The usual flow is: apply, complete the required qualification steps, join a project, finish the assigned work, and receive payment.

Time commitment

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

Compensation

Contributors can earn up to the equivalent of USD 58 per hour on this project, depending on skill level and working pace. Pay may differ across other projects based on scope, complexity, and expertise required.