Data Science Expert - AI Content Specialist

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

• 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 Tensor Flow 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

• 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

• 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

• 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