We are seeking experienced data scientists to create computationally intensive data science problems for an advanced AI evaluation project. This is a remote, project-based opportunity for experts who can design challenging problems that require computational methods to solve and mirror the full data science lifecycle - from data acquisition and processing to statistical analysis and actionable business insights.
What You'll Do
- Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare)
- Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn)
- Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks)
- Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction
- Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility
- Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency
- Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations)
- Incorporate big data processing scenarios requiring scalable computational approaches
- Verify solutions using Python with standard data science libraries and statistical methods
- Document problem statements clearly with realistic business contexts and provide verified correct answers