Data Science Expert – AI Content Specialist
About The Role
What if your deep knowledge of machine learning, statistics, and data engineering could directly shape how the world's most advanced AI systems think and reason? We're looking for Data Science Experts to stress-test, evaluate, and improve frontier AI models — identifying gaps in their reasoning and helping build smarter, more reliable systems.
This is a fully remote, flexible contract role designed for data science professionals who want meaningful, intellectually stimulating work on their own terms.
- 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 to expose the limits of AI reasoning.
- Author Ground-Truth Solutions — Develop rigorous, step-by-step technical solutions — including Python/R scripts, SQL queries, and mathematical derivations — that serve as authoritative benchmarks for AI evaluation.
- Audit AI-Generated Code — Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow, assessing correctness, efficiency, and best practices across data visualizations and statistical summaries.
- Refine Model Reasoning — Pinpoint logical failures such as data leakage, overfitting, and improper handling of imbalanced datasets, then deliver structured feedback that directly improves how AI models think.
Who You Are
- Advanced degree (Master's or PhD — pursuing or completed) in Data Science, Statistics, Computer Science, or a related quantitative discipline
- Strong domain expertise in supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), NLP, or similar areas
- Clear technical communicator — able to explain complex algorithms and statistical results in precise, accessible written form
- Detail-oriented — rigorous when reviewing code syntax, mathematical notation, and the validity of statistical conclusions
- No prior AI industry experience required — your data science knowledge is what matters
Nice to Have
- Experience with data annotation, data quality assessment, or evaluation systems
- Familiarity with production-level workflows such as MLOps or CI/CD for machine learning models
Why Join Us
- Work directly with industry-leading AI models and top research labs at the frontier of AI development
- Fully remote and asynchronous — work when and where it suits you
- Freelance autonomy with the substance of high-impact, technically rigorous work
- Contribute to AI systems that will influence how millions of people interact with technology
- Strong potential for ongoing contract engagement as new projects launch