Alignerr
Data Science Expert - AI Content Specialist
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Data Science Expert — AI Content Specialist
About The Role
What if your deep knowledge of machine learning, statistical modeling, 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 work alongside leading AI research labs, designing complex technical challenges and auditing AI-generated solutions to make frontier models smarter, more rigorous, and more reliable. This is a fully remote, flexible contract role built for practicing data scientists, researchers, and quantitative specialists who want to do meaningful work on their own schedule.
Organization: Alignerr
Type: Hourly Contract
Location: Remote
Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Challenges — Create complex, domain-rich data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
- Author Ground-Truth Solutions — Develop rigorous, step-by-step reference solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the benchmark for AI outputs
- Audit AI-Generated Code — Evaluate model-generated code using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and best practices
- Identify Reasoning Failures — Spot logical flaws in AI reasoning — data leakage, overfitting, improper handling of imbalanced datasets — and provide structured feedback to improve model reasoning
- Stress-Test Model Limits — Probe AI responses on topics like neural network architectures, statistical inference, and data engineering pipelines to surface and document failure modes
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Who You Are
- Holds or is pursuing a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field
- Strong foundational knowledge in supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP
- Able to communicate complex algorithmic concepts and statistical results clearly in written form
- Detail-oriented — precise when reviewing code syntax, mathematical notation, and the validity of statistical conclusions
- Self-directed and comfortable working independently in an async environment
- No prior AI or annotation experience required
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Nice to Have
- Experience with data annotation, data quality review, or evaluation systems
- Familiarity with production-level data science workflows — MLOps, CI/CD for models, or model monitoring
- Background in academic research or technical writing
Why Join Us
- Work directly with cutting-edge large language models and frontier AI research teams
- Fully remote and asynchronous — work when it suits you, from anywhere
- Freelance autonomy with meaningful, intellectually stimulating task-based work
- Contribute to AI development that shapes how models reason about real data science problems
- Potential for ongoing work and contract extension as new projects launch
“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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