Data Scientist (Masters)

Data Scientist (Masters) — AI Data Trainer
About The Role
What if your expertise in 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 scientists with advanced degrees to help train and evaluate cutting-edge AI models — stress-testing their reasoning, authoring gold-standard solutions, and catching the subtle flaws that separate good AI from great AI.
This is a fully remote, flexible contract role built for working data scientists, researchers, and advanced students who want to do meaningful, intellectually stimulating 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-specific data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
Author Ground-Truth Solutions — Write rigorous, step-by-step technical solutions — including Python/R scripts, SQL queries, and mathematical derivations — that serve as the benchmark AI models are trained against
Audit AI-Generated Code — Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and technical soundness
Identify Reasoning Failures — Spot and document logical errors in AI reasoning — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured feedback that sharpens model thinking
Improve Model Reasoning — Document failure modes and edge cases so AI systems can be hardened against real-world data science pitfalls
Who You Are
Pursuing or holding a Masters or PhD in Data Science, Statistics, Computer Science, or a quantitative field with strong emphasis on data analysis
Solid foundational knowledge across core areas — supervised/unsupervised learning, deep learning, statistical inference, or big data technologies like Spark and Hadoop
Able to communicate complex algorithmic and statistical concepts clearly and precisely in writing
Meticulous about code syntax, mathematical notation, and the validity of statistical conclusions
Self-directed and comfortable working independently on technical tasks
No prior AI training experience required
Nice to Have
Experience with data annotation, data quality evaluation, or AI evaluation workflows
Familiarity with production-level data science practices — MLOps, CI/CD for models, or model deployment pipelines
Background in NLP, computer vision, or other applied ML domains
Why Join Us
Work directly on projects with industry-leading AI research labs and LLMs
Fully remote and asynchronous — work when and where it suits you
Flexible hours and high contractor autonomy — you set the pace
Intellectually engaging work that keeps your technical skills sharp
Potential for ongoing contracts and project renewals as new AI initiatives launch