Data Scientist (Masters) — AI Data Trainer
About The Role
What if your deep knowledge of 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 expert-level data scientists to challenge, evaluate, and refine cutting-edge AI models — exposing their blind spots, correcting their reasoning, and helping build the next generation of intelligent systems.
This is a fully remote, flexible contract role. No prior AI industry experience required — just a strong foundation in data science and the ability to think rigorously under the hood.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Challenges — Craft 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 reference for AI evaluation
- Audit AI-Generated Code — Critically evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow — assessing technical accuracy, efficiency, and correctness
- Expose Reasoning Failures — Identify and document logical flaws in AI reasoning, such as data leakage, overfitting, or improper handling of imbalanced datasets, and provide structured feedback to improve model performance
Who You Are
- Currently 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
- Deeply knowledgeable in core data science domains — supervised/unsupervised learning, deep learning, statistical inference, big data technologies (Spark, Hadoop), or NLP
- A precise and analytical writer — you can explain complex algorithmic concepts and statistical results clearly in written form
- Naturally detail-oriented — you catch errors in code syntax, mathematical notation, and statistical logic that others miss
- No prior AI or data annotation experience required
Nice to Have
- Prior experience with data annotation, data quality, or AI evaluation workflows
- Proficiency in production-level data science practices — MLOps, CI/CD pipelines for models, or model monitoring
- Familiarity with evaluation rubrics or quality assurance processes in technical contexts
Why Join Us
- Work directly with industry-leading AI research labs on the frontier of model development
- Fully remote and asynchronous — work when and where it suits you
- High-agency contractor role with flexibility to scale your hours up or down
- Meaningful, intellectually stimulating work that puts your expertise to real use
- Potential for ongoing work and contract renewal as new projects launch
