Data Scientist (Masters)

Data Scientist (Masters) — AI Data Trainer
About The Role
What if your expertise in machine learning, statistical inference, and data engineering could directly shape how the world's most advanced AI systems think and reason? We're looking for data scientists with graduate-level training to stress-test cutting-edge AI models — designing the hardest problems you can imagine, building the gold-standard solutions, and identifying exactly where AI reasoning breaks down.
This is a fully remote, flexible contract role built for serious data scientists who want to work at the frontier of AI development — on their own schedule.
Organization: Alignerr
Type: Hourly Contract
Location: Remote
Commitment: 10–40 hours/week
What You'll Do
Design Advanced Challenges — Create rigorous, domain-specific data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
Build Ground-Truth Solutions — Author precise, step-by-step technical solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as definitive reference answers
Audit AI-Generated Code — Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and technical soundness
Sharpen AI Reasoning — Identify logical failures such as data leakage, overfitting, and improper handling of imbalanced datasets, then provide structured feedback that directly improves how models think
Work Independently — Complete task-based assignments asynchronously, fully on your own schedule
Who You Are
Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with strong emphasis on data analysis
Deep 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 and concisely in writing
Exceptionally detail-oriented — precise when checking code syntax, mathematical notation, and the validity of statistical conclusions
Self-motivated and consistent when working independently
No prior AI industry experience required
Nice to Have
Prior experience with data annotation, data quality evaluation, or AI output review
Proficiency in production-level data science workflows — MLOps, CI/CD for models, or model monitoring
Familiarity with academic or industry benchmarking methodologies
Broad exposure across multiple data science subfields
Why Join Us
Work directly with industry-leading AI research labs on cutting-edge model development
Fully remote and flexible — work when and where it suits you
High agency and autonomy as an independent contractor
Meaningful, intellectually stimulating work that pushes the boundaries of what AI can do
Potential for ongoing contract renewals as new projects launch

Work arrangement
No