Data Science Expert - AI Content Specialist

What You'll Do

• Design Advanced Challenges — Develop complex, expert-level data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
• Author Ground-Truth Solutions — Write rigorous, step-by-step technical solutions — including Python/R scripts, SQL queries, and mathematical derivations — that serve as the gold standard for model training
• Audit AI-Generated Code — Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for technical correctness, efficiency, and best practices
• Refine AI Reasoning — Identify logical failures in AI thinking — such as data leakage, overfitting, or mishandled class imbalance — and deliver structured feedback that improves model performance
• Stress-Test Model Limits — Push AI systems to their boundaries across machine learning theory, statistical inference, neural network architectures, and data engineering pipelines

Who You Are

• Hold or are pursuing a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field
• Strong foundational expertise in supervised/unsupervised learning, deep learning, big data technologies (Spark, Hadoop), or NLP
• Able to communicate complex algorithmic and statistical concepts clearly and precisely in writing
• Meticulous attention to detail — from code syntax to mathematical notation to the validity of statistical conclusions
• Self-directed and comfortable working independently on technical tasks
• No prior AI or annotation experience required

Nice to Have

• Experience with data annotation, data quality, or AI evaluation workflows
• Familiarity with production data science practices such as MLOps or CI/CD pipelines for models
• Prior work in academic research, technical writing, or quantitative analysis