Data Science Expert - AI Content Specialist

What You'll Do

• Create complex, domain-specific data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more.
• Develop rigorous, step-by-step reference solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the gold standard for AI evaluation.
• Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for technical correctness, efficiency, and best practices.
• Identify logical failures in AI-generated analysis — such as data leakage, overfitting, or mishandled class imbalance — and provide structured feedback that improves how models think and respond.

Who You Are

• Holds a Master's (pursuing or completed) or PhD in Data Science, Statistics, Computer Science, or a related quantitative field.
• Strong foundational expertise in areas such as supervised/unsupervised learning, deep learning, NLP, or big data technologies (Spark, Hadoop).
• Able to communicate complex algorithmic and statistical concepts clearly in writing.
• Precise and detail-oriented when reviewing code syntax, mathematical notation, and statistical conclusions.
• Self-motivated and comfortable working independently in an async, task-based environment.
• No prior AI or annotation experience required.

Nice to Have

• Experience with data annotation, data quality, or AI evaluation workflows.
• Familiarity with production-level data science practices — MLOps, CI/CD for models, model monitoring.
• Background in technical writing, research, or academic publishing.