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
Education & Core Experience
- Advanced degree (Master's or PhD) in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field
- 5+ years of hands-on data science experience with proven business impact
- Portfolio of completed projects and publications showcasing real-world problem-solving
Technical Skills
- Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels)
- Statistical analysis and machine learning - deep understanding of algorithms, methods, and their practical applications
- SQL and database operations for data manipulation and analysis
Modern AI/ML (Highly Valued)
- Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases)
- Understanding of MLOps practices and model deployment workflows
- Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain)
Professional Skills
- Ability to design problems reflecting real-world business scenarios and industry challenges
- Strong analytical and problem-solving skills with attention to detail
- Experience translating business requirements into technical solutions
- Clear technical writing and documentation skills
- Proficient in English for problem creation and communication
Preferred Qualifications
- Cross-industry experience (finance, telecommunications, healthcare, technology)
- Research background with publications or case studies
- Teaching, mentoring, or training experience
- Professional certifications in data science or machine learning
Application process
- Apply on the FRATCH platform and if you are being selected you will be provided with a short test by our client.
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