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 solve problems? We're looking for data scientists with advanced degrees to challenge, audit, and improve cutting-edge AI models — exposing their blind spots and helping build more rigorous, reliable intelligence.

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 — 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 definitive reference answers
• Audit AI-Generated Code — Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for technical accuracy, efficiency, and correctness
• Refine AI Reasoning — Identify and document logical failures — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured feedback that directly improves how models think

Who You Are

• Currently pursuing or have completed a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a strong emphasis on data analysis
• Deep foundational knowledge in core areas such as 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 written form
• Exceptionally detail-oriented — you catch errors in code syntax, mathematical notation, and statistical reasoning that others miss
• No prior AI or annotation experience required

Nice to Have

• Prior experience with data annotation, data quality evaluation, or model evaluation systems
• Proficiency in production-level data science workflows — MLOps, CI/CD for models, or similar
• Experience working across multiple modalities of data (tabular, text, image, time-series)

Why Join Us

• Work directly with industry-leading AI research labs on cutting-edge model development
• Fully remote and flexible — work on your own schedule, from anywhere in the world
• Freelance autonomy with meaningful, intellectually stimulating work
• High-impact contribution — your expertise directly shapes the reasoning capabilities of next-generation AI
• Potential for ongoing contract renewal as new projects launch