Data Science Expert - AI Content Specialist

Data Science Expert — AI Content Specialist
About The Role
What if your deep knowledge of machine learning, statistical modeling, and data engineering could directly shape how the world's most advanced AI systems think and reason?
We're looking for Data Science Experts to work alongside leading AI research labs, designing complex technical challenges and auditing AI-generated solutions to make frontier models smarter, more rigorous, and more reliable. This is a fully remote, flexible contract role built for practicing data scientists, researchers, and quantitative specialists who want to do meaningful work on their own schedule.
Organization: Alignerr
Type: Hourly Contract
Location: Remote
Commitment: 10–40 hours/week
What You'll Do
Design Advanced Challenges — Create 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 reference solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the benchmark for AI outputs
Audit AI-Generated Code — Evaluate model-generated code using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and best practices
Identify Reasoning Failures — Spot logical flaws in AI reasoning — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured feedback to improve model reasoning
Stress-Test Model Limits — Probe AI responses on topics like neural network architectures, statistical inference, and data engineering pipelines to surface and document failure modes
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 in supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP
Able to communicate complex algorithmic concepts and statistical results clearly in written form
Detail-oriented — precise when reviewing code syntax, mathematical notation, and the validity of statistical conclusions
Self-directed and comfortable working independently in an async environment
No prior AI or annotation experience required
Nice to Have
Experience with data annotation, data quality review, or evaluation systems
Familiarity with production-level data science workflows — MLOps, CI/CD for models, or model monitoring
Background in academic research or technical writing
Why Join Us
Work directly with cutting-edge large language models and frontier AI research teams
Fully remote and asynchronous — work when it suits you, from anywhere
Freelance autonomy with meaningful, intellectually stimulating task-based work
Contribute to AI development that shapes how models reason about real data science problems
Potential for ongoing work and contract extension as new projects launch

Work arrangement
No