About the job
Please submit your CV in English and indicate your English proficiency level.
This freelance, project-based role with Mindrift connects experienced data science professionals to AI projects for leading technology companies. Assignments focus on testing, evaluating, and improving AI systems. This is not a permanent position.
Role overview
The Freelance Data Science Engineer (Python & SQL) creates and validates computational data science challenges for real-world business applications. Projects are varied and may include:
- Designing original data science problems that reflect analytical processes in industries such as telecom, finance, government, e-commerce, and healthcare.
- Developing tasks requiring Python programming with libraries like Pandas, Numpy, Scipy, Sklearn, Statsmodels, Matplotlib, and Seaborn.
- Ensuring challenges are computationally intensive and not solvable manually within days or weeks.
- Formulating problems involving complex reasoning in data processing, statistical analysis, feature engineering, predictive modeling, and insight generation.
- Designing deterministic problems with reproducible results, either by avoiding randomness or using fixed random seeds.
- Basing scenarios on genuine business needs such as customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.
- Covering the full data science pipeline, from data ingestion and cleaning to exploratory analysis, modeling, validation, and deployment considerations.
- Introducing big data scenarios that require scalable computational approaches.
- Validating solutions using Python, established data science libraries, and statistical methods.
- Documenting problem statements in realistic business contexts and providing verified solutions.
Requirements
- Minimum 5 years of hands-on data science experience with measurable business outcomes.
- Portfolio of completed projects or publications that demonstrate real-world problem-solving.
- Expertise in Python for data science (including pandas, numpy, scipy, scikit-learn, statsmodels).
- Strong background in statistical analysis and machine learning, with practical knowledge of algorithms.
- Proficiency in SQL and database operations for data analysis.
- Familiarity with GenAI technologies, such as LLMs, RAG, prompt engineering, and vector databases.
- Understanding of MLOps practices and model deployment workflows.
- Experience with frameworks like TensorFlow, PyTorch, or LangChain.
- Excellent written English skills (C1 level or higher).
How the process works
- Apply
- Meet qualifications
- Join a project
- Complete assigned tasks
- Receive payment
Location: Remote, Greece
