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About the Role
Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. This is a project-based opportunity rather than permanent employment.
Responsibilities
- Design original computational data science problems simulating real-world analytical workflows
- Create problems requiring Python programming using standard data science libraries
- Ensure problems are computationally intensive and require non-trivial reasoning chains
- Develop deterministic problems with reproducible answers
- Base problems on real business challenges such as fraud detection, forecasting, and optimization
- Design end-to-end problems spanning the complete data science pipeline
- Incorporate big data processing scenarios requiring scalable computational approaches
- Verify solutions using Python and statistical methods
- Document problem statements clearly with realistic business contexts and provide verified answers
Requirements
- Submit CV in English
- Indicate level of English proficiency
- 5+ years of hands-on data science experience with proven business impact
- Portfolio of completed projects and publications
- Expert Python programming for data science
- Expert statistical analysis and machine learning knowledge
- Expert with SQL and database operations
- Experience with GenAI technologies including LLMs, RAG, and vector databases
- Understanding of MLOps practices and model deployment
- Knowledge of modern frameworks like TensorFlow, PyTorch, and LangChain
- Strong written English proficiency at C1 level or higher
Skills
- Python
- Pandas
- Numpy
- Scipy
- Scikit-learn
- Statsmodels
- Matplotlib
- Seaborn
- SQL
- GenAI
- LLMs
- RAG
- Prompt engineering
- Vector databases
- MLOps
- TensorFlow
- PyTorch
- LangChain
Work Type
- Project-based
- Part-time
- Non-permanent
Experience Level
- 5+ years
Salary/Compensations
- Up to $58 per hour
About the Company
- Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.