Alignerr
Data Scientist (Masters)
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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 thinks and reasons?
We're looking for data scientists with advanced training to help build and stress-test cutting-edge AI models. You'll design the kinds of complex, expert-level challenges that push AI systems to their limits — and when they fail, you'll document exactly why, so we can make them better.
This is a fully remote, flexible contract role. No prior AI industry experience required — just serious domain expertise 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 expert-level 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 AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for technical correctness, efficiency, and best practices
- Sharpen AI Reasoning — Identify logical failures in AI responses — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured feedback that directly improves model reasoning
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Who You Are
- Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field
- Strong foundational knowledge across supervised and 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-motivated and comfortable working independently on an async schedule
- No prior AI or data annotation experience required
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Nice to Have
- Experience with data annotation, data quality systems, or model evaluation
- Familiarity with production-level data science workflows — MLOps, CI/CD pipelines for models
- Exposure to multiple programming languages and statistical environments
Why Join Us
- Work directly alongside industry-leading AI research labs on genuinely frontier technology
- Fully remote and asynchronous — work when and where it suits you
- Freelance autonomy with meaningful, intellectually stimulating work
- High-impact role where your expertise shapes how advanced AI understands data science
- Potential for ongoing contracts and expanded project opportunities as new work launches
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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