Data Science Expert - AI Content Specialist

Data Science Expert – AI Content Specialist
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

Work arrangement
Yes