Data Scientist (Masters)

Data Scientist (Masters) — AI Data TrainerAbout The RoleWhat if your deep knowledge of 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 advanced degrees to work alongside leading AI research labs — designing expert-level challenges, authoring rigorous solutions, and auditing AI-generated code to make models smarter, more accurate, and more reliable.This is a fully remote, flexible contract role. No prior AI industry experience required — just serious domain expertise and a sharp analytical mind.Organization: AlignerrType: Hourly ContractLocation: RemoteCommitment: 10–40 hours/weekWhat You'll DoDesign Advanced Challenges — Create complex, domain-spanning data science problems covering hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and moreAuthor Ground-Truth Solutions — Develop rigorous, step-by-step technical solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the gold standard for AI trainingAudit AI-Generated Code — Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for technical accuracy, efficiency, and correctnessRefine AI Reasoning — Identify logical flaws such as data leakage, overfitting, or improper handling of imbalanced datasets and provide structured feedback to sharpen model thinkingDocument Failure Modes — Probe advanced language models on topics like neural network architectures and data engineering pipelines, capturing and reporting every reasoning gapWho You ArePursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a strong data analysis focusStrong foundational knowledge across supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLPAble to communicate highly technical algorithmic and statistical concepts clearly and concisely in writingExceptionally detail-oriented when reviewing code syntax, mathematical notation, and the validity of statistical conclusionsSelf-directed and comfortable working independently on an async scheduleNo prior AI or data annotation experience requiredNice to HaveExperience with data annotation, data quality assurance, or AI evaluation systemsProficiency in production-level data science workflows — MLOps, CI/CD for models, or similarFamiliarity with model evaluation frameworks or benchmarking methodologiesWhy Join UsWork directly on cutting-edge AI projects alongside world-leading research labsFully remote and async — work when and where it suits youFreelance autonomy with meaningful, intellectually stimulating workDirect, hands-on engagement with industry-leading large language modelsPotential for ongoing contract renewals as new projects launch