Data Science Expert — AI Content Specialist
About The Role
What if your deep knowledge of machine learning, statistical inference, and data engineering could directly influence how the world's most advanced AI models reason and respond
We're looking for experienced data scientists to join Alignerr's expert network and help train cutting-edge AI systems. You'll stress-test model reasoning, author gold-standard solutions, and provide the kind of rigorous technical feedback that makes AI genuinely smarter. This is meaningful, intellectually engaging work — done entirely on your terms, from anywhere in the world.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Challenges — Create complex, domain-specific 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 authoritative reference responses
- Audit AI-Generated Code — Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and best practices
- Sharpen AI Reasoning — Identify logical failures such as data leakage, overfitting, or improper handling of imbalanced datasets, and provide structured feedback that directly improves how AI models think
Who You Are
- Currently pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field
- 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
- Precise and detail-oriented when reviewing code syntax, mathematical notation, and statistical conclusions
- No prior AI or annotation experience required
Nice to Have
- Experience with data annotation, data quality assurance, or evaluation systems
- Familiarity with production-level data science workflows, including MLOps or CI/CD for models
- Hands-on experience deploying or monitoring models in real-world environments
Why Join Us
- Work directly with industry-leading AI systems and contribute to research that shapes the future of machine intelligence
- Fully remote and async — work on your own schedule, from anywhere
- Freelance flexibility with the consistency of ongoing, meaningful project work
- High-agency contracting with opportunities for project renewals and expanded engagement
- Be part of a global expert network working alongside top AI research labs
