Data Science Expert - AI Content Specialist
Data & Analytics / STEM / Software & Coding
$40-$80/hr
About this role · Stem
About the Role What if your data science knowledge could directly shape the intelligence of tomorrow's most advanced AI systems? We're looking for Data Science Experts to stress-test, evaluate, and improve cutting-edge language models — exposing their blind spots, correcting their reasoning, and setting the standard for what great data science looks like. This is a fully remote, flexible contract role designed for experienced data scientists, statisticians, and ML practitioners who want to do meaningful, intellectually stimulating work on their own schedule. - Organization: Alignerr - Type: Hourly Contract - Location: Remote - Commitment: 10–40 hours/week What You'll Do - Design Advanced Challenges — Develop complex, domain-specific 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 definitive "gold standard" responses - Audit AI-Generated Code — Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and best practices - Sharpen AI Reasoning — Identify logical failures in AI outputs — data leakage, overfitting, improper handling of imbalanced datasets — and deliver structured feedback that improves how models think Who You Are - Holds or is pursuing a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with heavy emphasis on data analysis - Strong foundational knowledge across core areas: supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP - Able to communicate complex algorithmic and statistical concepts clearly and concisely in writing - Highly precise when reviewing code syntax, mathematical notation, and statistical conclusions - Self-motivated and reliable when working independently on task-based assignments - No prior AI or annotation experience required Nice to Have - Experience with data annotation, data quality assurance, or evaluation systems - Proficiency in production-level data science workflows such as MLOps or CI/CD for models - Familiarity with prompt engineering or working alongside AI systems Why Join Us - Work directly with industry-leading AI language models at the frontier of AI research - Fully remote and async — work when and where you perform best - Freelance autonomy with the structure of meaningful, technically challenging work - Contribute to AI development that has a real impact on how these systems reason about data science - Potential for ongoing work and contract extension as new projects launch