Data Science Expert - AI Content Specialist

Data Science Expert — AI Content Specialist
About The Role
What if your deep knowledge of machine learning, statistics, and data engineering could directly shape how the world's most advanced AI systems reason and respond?
We're looking for Data Science Experts to work with Alignerr — a team that partners with leading AI research labs to build and refine cutting-edge language models. Your job is to stress-test AI reasoning, author gold-standard solutions, and provide the kind of expert feedback that makes these models genuinely smarter.
This is a fully remote, flexible contract role built for data science professionals who want 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 — 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 benchmark for AI responses
Audit AI-Generated Code — Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow, assessing them for correctness, efficiency, and best practices
Sharpen AI Reasoning — Identify logical failures such as data leakage, overfitting, or improper handling of imbalanced datasets, and deliver structured feedback that improves how models think
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 expertise in core areas such as supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP
Able to communicate complex algorithmic concepts and statistical findings clearly in writing
Highly precise when reviewing code syntax, mathematical notation, and the validity of statistical conclusions
No prior AI or annotation experience required — your domain expertise is what matters
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 for models
Why Join Us
Work directly with industry-leading AI language models on problems that actually matter
Fully remote and asynchronous — work when and where it suits you
Freelance autonomy with the structure of meaningful, task-based projects
Contribute to AI development that shapes how these systems reason through real-world data science problems
Potential for ongoing work and contract extension as new projects launch

Work arrangement
No