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 AI systems? We're looking for Data Science Experts to stress-test, evaluate, and improve advanced AI models — exposing gaps in their reasoning and helping build more accurate, reliable machine learning capabilities. This is a fully remote, flexible contract role built for experienced data scientists and quantitative researchers who want 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: Craft complex, domain-rich data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more — specifically engineered to probe the limits of AI reasoning - Author Ground-Truth Solutions: Develop rigorous, step-by-step reference solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the definitive standard for model evaluation - Audit AI-Generated Code: Review and assess AI outputs across libraries like Scikit-Learn, PyTorch, and TensorFlow — evaluating technical accuracy, efficiency, and correctness of data visualizations and statistical summaries - Refine AI Reasoning: Identify subtle logical failures — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured, actionable feedback that directly 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 discipline with a strong data focus - Deep knowledge across core areas: supervised/unsupervised learning, deep learning, NLP, or big data technologies (Spark, Hadoop) - Able to communicate complex algorithmic and statistical concepts clearly and precisely in writing - Exceptionally detail-oriented — code syntax, mathematical notation, and statistical validity all matter to you - No prior AI or annotation experience required Nice to Have - Experience with data annotation, quality evaluation, or labeling systems - Familiarity with production-level data science workflows — MLOps, CI/CD for models, experiment tracking - Background in academic research or technical writing Why Join Us - Work directly with industry-leading AI language models at the frontier of research - Fully remote and asynchronous — work when and where you perform best - Freelance flexibility with consistent, substantive task-based work - Contribute to AI development that has a real and lasting impact on how models reason about data science - Potential for ongoing work and contract extension as new projects launch