Data Scientist (Masters) – AI Data Trainer

Job Description

What You’ll Do

• Develop Complex Problems: Design advanced data science challenges across domains like hyperparameter optimization, Bayesian inference, cross-validation strategies, and dimensionality reduction.
• Author Ground-Truth Solutions: Create rigorous, step-by-step technical solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as “golden responses.”
• Technical Auditing: Evaluate AI-generated code (using libraries like Scikit-Learn, PyTorch, or TensorFlow), data visualizations, and statistical summaries for technical accuracy and efficiency.
• Refine Reasoning: Identify logical fallacies in AI reasoning—such as data leakage, overfitting, or improper handling of imbalanced datasets—and provide structured feedback to improve the model’s “thinking” process.

Requirements

• Advanced Degree: Masters (pursuing or completed) or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a heavy emphasis on data analysis.
• Domain Expertise: Strong foundational knowledge in core areas such as supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP.
• Analytical Writing: The ability to communicate highly technical algorithmic concepts and statistical results clearly and concisely in written form.
• Attention to Detail: High level of precision when checking code syntax, mathematical notation, and the validity of statistical conclusions.
• No AI experience required

Preferred

• Prior experience with data annotation, data quality, or evaluation systems
• Proficiency in production-level data science workflows (e.g., MLOps, CI/CD for models).

Are you interested in this position?

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