Data Scientist (Masters)

Data Scientist (Masters) - AI Data TrainerAbout 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 reason and problem-solve? We're looking for data scientists with graduate-level training to challenge, audit, and refine cutting-edge AI models - exposing their blind spots and building the ground-truth solutions that make them smarter.This is a fully remote, flexible contract role. No prior AI industry experience needed - just deep, rigorous command of data science and a sharp eye for technical accuracy.Organization: AlignerrType: Hourly ContractLocation: RemoteCommitment: 10-40 hours/weekWhat You'll Do
Design Complex Challenges - Develop advanced data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and moreAuthor Ground-Truth Solutions - Write rigorous, step-by-step technical solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as definitive reference answersAudit AI-Generated Code - Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and technical soundnessSharpen AI Reasoning - Identify logical failures in AI reasoning - data leakage, overfitting, improper handling of imbalanced datasets - and deliver structured feedback that directly improves how these models thinkDocument Failure Modes - Systematically record how and where advanced language models break down on data science tasks, helping research teams harden model reliabilityWho You Are
Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative discipline with a strong data focusDeeply fluent in core data science concepts: supervised and unsupervised learning, deep learning, statistical inference, and big data technologiesAble to translate complex algorithmic concepts and statistical results into clear, precise written explanationsExceptionally detail-oriented - you catch errors in code syntax, mathematical notation, and statistical conclusions that others missComfortable working independently and asynchronously without hand-holdingNo prior AI or data annotation experience requiredNice to Have
Experience with data annotation, data quality evaluation, or AI model assessment workflowsProficiency in production data science environments - MLOps, CI/CD for models, model monitoringFamiliarity with NLP, computer vision, or large-scale distributed computing (Spark, Hadoop)Background in technical writing, research, or academic publishingWhy Join Us
Work directly with industry-leading AI research teams and cutting-edge language modelsFully remote and flexible - structure your hours around your lifeFreelance autonomy with meaningful, intellectually stimulating workContribute to AI development that shapes the future of data science reasoning at scalePotential for ongoing contract renewals as new projects launch
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