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 respond?

We're looking for experienced data scientists to challenge, audit, and improve cutting-edge AI models — pushing them to their limits, exposing their blind spots, and building the gold-standard solutions that make them smarter. This is a fully remote, flexible contract role where your deep technical knowledge does meaningful work at the frontier of AI development.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 10–40 hours/week

What You'll Do

• Design Advanced Challenges — Create complex, domain-specific data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
• Author Ground-Truth Solutions — Develop rigorous, step-by-step technical solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the definitive benchmark for AI responses
• Audit AI-Generated Code — Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for technical accuracy, efficiency, and correctness
• Sharpen AI Reasoning — Identify logical failures in AI outputs — data leakage, overfitting, improper handling of imbalanced datasets — and deliver structured feedback that improves model reasoning
• Document Failure Modes — Stress-test model responses across ML theory, statistical inference, neural network architectures, and data engineering pipelines, capturing every gap so models can be hardened

Who 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 analysis
• Strong foundational knowledge in supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP
• Able to communicate complex algorithmic concepts and statistical results clearly and precisely in writing
• Detail-oriented — you catch errors in code syntax, mathematical notation, and statistical conclusions that others miss
• Self-directed and reliable when working independently on technical tasks
• No prior AI industry experience required

Nice to Have

• Prior experience with data annotation, data quality assurance, or model evaluation systems
• Proficiency in production-level data science workflows — MLOps, CI/CD for models, experiment tracking
• Familiarity with prompt engineering or AI benchmarking methodologies

Why Join Us

• Work at the cutting edge of AI development alongside world-leading research labs
• Fully remote and asynchronous — work when and where it suits you
• Freelance autonomy with meaningful, technically stimulating work
• Direct hands-on engagement with the most advanced language models in the field
• Potential for ongoing contract renewals as new AI projects launch