About the job
Please submit your CV in English and include your English proficiency level.
Toloka AI, in partnership with Mindrift, offers project-based freelance opportunities for skilled professionals to help test, evaluate, and improve AI systems for leading technology companies. This is a freelance, project-based position and does not lead to permanent employment.
Role overview
As a Freelance AI Trainer (Data Scientist) working remotely from Sweden, assignments focus on building and refining AI models through real-world data science challenges. Typical projects include:
- Designing computational data science problems that mirror analytical workflows in sectors like telecom, finance, government, e-commerce, and healthcare.
- Developing problems that require Python solutions, using libraries such as Pandas, Numpy, Scipy, Scikit-learn, Statsmodels, Matplotlib, and Seaborn.
- Ensuring problems are computationally demanding, taking days or weeks to solve, and not just manual calculations.
- Creating scenarios that call for complex reasoning in data processing, statistical analysis, feature engineering, predictive modeling, and drawing insights.
- Making sure all challenges are deterministic and reproducible, either by avoiding randomness or by using fixed random seeds.
- Basing tasks on real business needs, including customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.
- Covering the full data science workflow: data ingestion, cleaning, exploratory analysis, modeling, validation, and deployment considerations.
- Including big data processing scenarios that need scalable computational approaches.
- Validating solutions in Python with standard data science libraries and statistical techniques.
- Documenting problem statements clearly, with realistic business contexts and verified solutions.
Requirements
- Minimum 5 years of hands-on data science experience with demonstrated business impact.
- A portfolio of completed projects or publications showing real-world problem solving.
- Advanced Python skills for data science (including pandas, numpy, scipy, scikit-learn, statsmodels).
- Strong background in statistical analysis and machine learning, with deep knowledge of algorithms and their uses.
- Proficiency in SQL and database operations for data manipulation and analysis.
- Experience with Generative AI, such as LLMs, Retrieval-Augmented Generation, prompt engineering, and vector databases.
- Understanding of MLOps and model deployment processes.
- Familiarity with frameworks like TensorFlow, PyTorch, and LangChain.
- Excellent written English (C1 level or higher).
How to apply
- Apply
- Complete qualifications
- Join a project
- Fulfill tasks
- Receive payment

