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 think and reason? We're looking for data scientists with graduate-level training to challenge, evaluate, and improve cutting-edge AI models — exposing their blind spots and helping them reason more rigorously about complex technical problems.
This is a fully remote, flexible contract role. No prior AI industry experience required — just deep domain knowledge and a sharp analytical mind.
Organization: Alignerr
Type: Hourly Contract
Location: Remote
Commitment: 10–40 hours/week
What You'll Do
Design Advanced Challenges: Craft sophisticated data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more — pushing AI models to their limits
Author Ground-Truth Solutions: Write rigorous, 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 AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow — assessing correctness, efficiency, and technical soundness
Refine Model Reasoning: Identify flaws in AI reasoning such as data leakage, overfitting, and improper handling of imbalanced datasets, then provide structured, actionable feedback to improve how models think
Document Failure Modes: Systematically record edge cases and reasoning errors to help harden model performance across real-world data science scenarios
Who You Are
Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with strong emphasis on data analysis
Solid foundational knowledge across supervised and unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP
Able to communicate complex algorithmic concepts and statistical results clearly in written form
Naturally precise — you catch errors in code syntax, mathematical notation, and statistical conclusions
Self-directed and comfortable working independently on technical tasks
No prior AI or 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 pipelines for models, or model monitoring
Background in technical writing or academic research communication
Why Join Us
Work directly with industry-leading AI models and top-tier research labs
Fully remote and flexible — work when and where it suits you
Freelance autonomy with meaningful, intellectually stimulating work
High agency over your schedule with 10–40 hours per week based on your availability
Potential for ongoing contract renewals as new AI projects launch

Work arrangement
No