Data Scientist (Masters)

Data Scientist (Masters) — AI Model TrainerAbout The RoleWhat if your expertise in machine learning, statistical inference, and data engineering could directly shape how the world's most advanced AI systems reason through complex problems? We're looking for data scientists with advanced degrees to challenge, audit, and refine cutting-edge AI models — helping them think more rigorously, reason more accurately, and perform at a higher level.This is a fully remote, flexible contract role. No prior AI industry experience required — just deep domain knowledge and a sharp analytical mind.Organization: AlignerrType: Hourly ContractLocation: RemoteCommitment: 10–40 hours/weekWhat You'll DoDesign Advanced Challenges: Develop complex, domain-specific data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more — problems that genuinely push AI reasoning to its limitsAuthor Ground-Truth Solutions: Write rigorous, step-by-step technical solutions including Python and R scripts, SQL queries, and mathematical derivations that serve as authoritative reference answersAudit AI-Generated Code: Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow — assessing them for technical accuracy, efficiency, and correctnessIdentify and Document Failure Modes: Catch logical errors in AI reasoning such as data leakage, overfitting, and improper handling of imbalanced datasets, then provide structured feedback that improves model behaviourRefine Model Reasoning: Help shape how AI models approach statistical and algorithmic problems by documenting every meaningful failure and guiding iterative improvementsWho You AreCurrently pursuing or have completed a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a strong data analysis focusSolid foundational knowledge across core areas such as supervised and unsupervised learning, deep learning, big data technologies (Spark, Hadoop), or NLPAble to communicate highly technical concepts — algorithmic logic, statistical results, mathematical derivations — clearly and precisely in written formNaturally detail-oriented: you catch errors in code syntax, mathematical notation, and statistical reasoning that others missSelf-directed and comfortable working independently on technical tasksNo prior AI or data annotation experience requiredNice to HavePrior experience with data annotation, data quality assurance, or model evaluation systemsProficiency in production-level data science workflows such as MLOps or CI/CD pipelines for machine learning modelsFamiliarity with prompt engineering or working with large language modelsExperience writing technical documentation or academic-style explanations of complex methodsWhy Join UsWork directly with industry-leading AI research teams and language models at the frontier of the fieldFully remote and flexible — work when and where it suits you, on your own scheduleFreelance autonomy with the structure of meaningful, technically rigorous workMake a direct, measurable impact on how the next generation of AI understands and applies data sciencePotential for ongoing work and contract extension as new projects launch