Data Scientist (Masters)

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 systems reason and problem-solve? We're looking for Masters-level data scientists to challenge, evaluate, and refine cutting-edge AI models — stress-testing their reasoning on the hardest problems your field has to offer. This is a fully remote, flexible contract role. No prior AI industry experience needed — just deep domain knowledge and a sharp eye for technical accuracy. • Organization: Alignerr • Type: Hourly Contract • Location: Remote • Commitment: 10–40 hours/week What You'll Do • Design Advanced Challenges — Create rigorous data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more • Author Ground-Truth Solutions — Write precise, step-by-step technical solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as definitive reference answers • Audit AI-Generated Code — Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and best practices • Identify Reasoning Failures — Spot and document logical flaws in AI reasoning — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured feedback to improve model behavior • Work Independently — Complete task-based assignments asynchronously, fully on your own schedule Who You Are • Currently pursuing or holding a Masters or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a strong emphasis on data analysis • Solid foundational knowledge across core areas such as supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP • Able to communicate complex algorithmic concepts and statistical findings clearly and concisely in writing • Precise and detail-oriented — you notice when code logic, mathematical notation, or statistical conclusions don't hold up • No prior AI or data annotation experience required Nice to Have • Experience with data annotation, data quality assurance, or evaluation systems • Familiarity with production-level data science workflows — MLOps, CI/CD for models, or model monitoring • Background in academic research, technical writing, or peer review • Hands-on experience with experiment tracking tools like MLflow or Weights & Biases Why Join Us • Work directly with industry-leading AI research labs on genuinely cutting-edge models • Fully remote and flexible — work when and where it suits you • Freelance autonomy with the structure of meaningful, high-impact technical work • Engage deeply with topics at the frontier of machine learning and AI development • Potential for ongoing work and contract extension as new projects launch