About the job
Please submit your CV in English and indicate your English proficiency level.
toloka-ai, in partnership with Mindrift, connects professionals to project-based freelance roles focused on testing, evaluating, and improving AI systems for leading technology companies. All roles are freelance and project-based, not permanent employment.
Role overview
This Freelance Data Science Engineer position centers on designing and validating advanced computational problems for real-world analytics. Projects span sectors such as telecom, finance, government, e-commerce, and healthcare. The work is fully remote and open to candidates based in Austria.
What you will do
- Design computational data science problems that reflect actual business workflows across multiple industries.
- Develop solutions in Python using libraries such as Pandas, Numpy, Scipy, Sklearn, Statsmodels, Matplotlib, and Seaborn.
- Create complex, algorithmic problems that require computational rather than manual solutions.
- Build data processing challenges involving statistical analysis, feature engineering, predictive modeling, and insight extraction.
- Ensure problems are deterministic and reproducible by avoiding randomness or using fixed seeds.
- Base challenges on real business scenarios, including customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.
- Design problems that cover the full data science pipeline: data ingestion, cleaning, exploratory analysis, modeling, validation, and deployment considerations.
- Include big data processing cases that require scalable computation.
- Validate solutions in Python using standard libraries and statistical methods.
- Document each problem with clear business context and verified answers.
Requirements
- Minimum 5 years of hands-on data science experience with measurable business impact.
- Portfolio of completed projects or publications demonstrating real-world problem-solving.
- Advanced Python programming skills for data science, including pandas, numpy, scipy, scikit-learn, and statsmodels.
- Strong background in statistical analysis and machine learning, with deep understanding of algorithms and methodologies.
- Expertise in SQL and database operations for data manipulation and analysis.
- Familiarity with Generative AI, such as large language models, retrieval-augmented generation, prompt engineering, and vector databases.
- Knowledge of MLOps practices and model deployment workflows.
- Experience with frameworks like TensorFlow, PyTorch, and LangChain.
- Excellent written English skills at C1 level or higher.
Application process
- Apply
- Pass qualifications
- Join a project
- Complete tasks
- Receive compensation
