Data Scientist (Masters)
Alignerr Corp.
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 models think and reason? We're looking for Masters-level data scientists to challenge, stress-test, and refine cutting-edge AI systems — helping ensure they reason correctly, write clean code, and handle complex problems with precision.This is a fully remote, flexible contract role. No prior AI industry experience needed — just deep domain knowledge, sharp analytical instincts, and the ability to communicate technical concepts clearly.What You'll Do
Design complex data science challenges across domains like hyperparameter optimization, Bayesian inference, cross-validation strategies, and dimensionality reduction — pushing AI models to their limitsAuthor rigorous ground-truth solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the gold standard for model evaluationAudit AI-generated code and outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow — assessing technical accuracy, efficiency, and correctnessIdentify and document reasoning failures such as data leakage, overfitting, and improper handling of imbalanced datasets, then provide structured feedback to sharpen model reasoningWork independently and asynchronously — fully on your own scheduleWho You Are
Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a strong emphasis on data analysisDeeply knowledgeable in core areas such as supervised and unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLPAble to write clearly and precisely about complex algorithmic concepts and statistical results for technical audiencesNaturally detail-oriented — you catch errors in code syntax, mathematical notation, and statistical reasoning that others missSelf-motivated and consistent when working independentlyNo prior AI or data annotation experience requiredNice to Have
Experience with data annotation, data quality evaluation, or AI evaluation systemsProficiency in production-level data science workflows such as MLOps or CI/CD for modelsFamiliarity with model benchmarking or technical content authoringBackground spanning multiple data science subfields — the broader your expertise, the more impactful your contributionsWhy Join Us
Work directly with industry-leading AI research labs on cutting-edge model developmentFully remote and flexible — work when and where it suits youFreelance autonomy with the structure of meaningful, task-based workMake a direct, tangible impact on how advanced AI models reason about data sciencePotential for ongoing work and contract extension as new projects launch
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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 models think and reason? We're looking for Masters-level data scientists to challenge, stress-test, and refine cutting-edge AI systems — helping ensure they reason correctly, write clean code, and handle complex problems with precision.This is a fully remote, flexible contract role. No prior AI industry experience needed — just deep domain knowledge, sharp analytical instincts, and the ability to communicate technical concepts clearly.What You'll Do
Design complex data science challenges across domains like hyperparameter optimization, Bayesian inference, cross-validation strategies, and dimensionality reduction — pushing AI models to their limitsAuthor rigorous ground-truth solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the gold standard for model evaluationAudit AI-generated code and outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow — assessing technical accuracy, efficiency, and correctnessIdentify and document reasoning failures such as data leakage, overfitting, and improper handling of imbalanced datasets, then provide structured feedback to sharpen model reasoningWork independently and asynchronously — fully on your own scheduleWho You Are
Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a strong emphasis on data analysisDeeply knowledgeable in core areas such as supervised and unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLPAble to write clearly and precisely about complex algorithmic concepts and statistical results for technical audiencesNaturally detail-oriented — you catch errors in code syntax, mathematical notation, and statistical reasoning that others missSelf-motivated and consistent when working independentlyNo prior AI or data annotation experience requiredNice to Have
Experience with data annotation, data quality evaluation, or AI evaluation systemsProficiency in production-level data science workflows such as MLOps or CI/CD for modelsFamiliarity with model benchmarking or technical content authoringBackground spanning multiple data science subfields — the broader your expertise, the more impactful your contributionsWhy Join Us
Work directly with industry-leading AI research labs on cutting-edge model developmentFully remote and flexible — work when and where it suits youFreelance autonomy with the structure of meaningful, task-based workMake a direct, tangible impact on how advanced AI models reason about data sciencePotential for ongoing work and contract extension as new projects launch
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Vacancy posted 1 hour ago
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