Data Scientist (Masters)

About the role

This is a fully remote, flexible contract role.

What You'll Do

• Design Advanced Challenges — Create complex, real-world 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 reference answers for AI training
• Audit AI-Generated Code — Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and technical soundness
• Identify Reasoning Failures — Catch logical errors in AI reasoning — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured feedback that improves how models think
• Work Independently — Complete task-based assignments asynchronously on your own schedule

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
• Deeply fluent in core ML concepts — supervised/unsupervised learning, deep learning, probabilistic modeling, and statistical inference
• Comfortable working across big data technologies (Spark, Hadoop) and/or NLP frameworks
• Able to communicate complex algorithmic concepts and statistical results clearly in writing
• Precise and thorough — you catch errors in code syntax, mathematical notation, and statistical conclusions
• No prior AI training or annotation experience required

Nice to Have

• Experience with data annotation, data quality pipelines, or model evaluation systems
• Proficiency in production-level data science workflows — MLOps, CI/CD for models, or similar
• Background in academic research or technical writing