Data Science Expert - AI Content Specialist

Data Science Expert – AI Content Specialist
About The Role
What if your expertise in machine learning and statistical modeling could directly shape how the world's most advanced AI systems think and reason?
We're looking for experienced data scientists to work alongside leading AI research labs — designing challenges that push AI to its limits, authoring gold-standard solutions, and identifying the subtle reasoning failures that prevent AI from reaching its full potential.
This is a fully remote, flexible contract role. Your domain knowledge isn't just useful here — it's the whole point.
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
Author Ground-Truth Solutions — Develop rigorous, step-by-step technical solutions — including Python/R scripts, SQL queries, and mathematical derivations — that serve as the definitive benchmark for AI responses
Audit AI-Generated Code — Evaluate outputs from models using Scikit-Learn, PyTorch, TensorFlow, and other major libraries for correctness, efficiency, and best practices
Refine AI Reasoning — Spot logical failures like data leakage, overfitting, and improper handling of class imbalance, then provide structured feedback that improves how AI models reason through problems
Document Failure Modes — Systematically record where and how AI reasoning breaks down to help research teams build more robust models
Who You Are
Holds or is pursuing a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field
Strong foundational knowledge across supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP
Able to communicate complex algorithmic and statistical concepts clearly in writing
Meticulous attention to detail — especially when reviewing code syntax, mathematical notation, and statistical validity
Self-directed and comfortable working independently on technical tasks
No prior AI or annotation experience required
Nice to Have
Experience with data annotation, data quality workflows, or evaluation systems
Familiarity with production-level data science practices such as MLOps or CI/CD pipelines for models
Why Join Us
Work directly with industry-leading AI language models at the frontier of AI research
Fully remote and async-friendly — work on your own schedule, from anywhere
Freelance autonomy with meaningful, intellectually stimulating work
Contribute to AI development that has a real and lasting impact on how AI reasons about data and science
Strong potential for ongoing work and contract renewal as new projects launch

Work arrangement
Yes