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 work with Alignerr — a team that partners with leading AI research labs to train and refine cutting-edge language models. You’ll stress-test AI reasoning, author gold-standard solutions, and help eliminate the kinds of subtle errors — data leakage, overfitting, flawed statistical inference — that make AI unreliable in real-world applications.
This is a fully remote, flexible contract role designed for experienced data science professionals who want meaningful, intellectually engaging work on their own schedule.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You’ll Do
- Design Advanced Challenges — Craft rigorous, domain-specific data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
- Author Ground-Truth Solutions — Produce authoritative, step-by-step technical solutions — including Python/R scripts, SQL queries, and mathematical derivations — that serve as benchmark responses for model training
- Audit AI-Generated Code — Evaluate model outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for correctness, efficiency, and best practices
- Refine AI Reasoning — Identify logical flaws in model outputs such as data leakage, class imbalance mishandling, or improper train/test splits, and provide structured feedback to improve model reasoning
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 across core areas: supervised/unsupervised learning, deep learning, statistical inference, and/or big data technologies (Spark, Hadoop)
- Able to communicate complex algorithmic and statistical concepts clearly in written form
- Highly precise — comfortable checking code syntax, mathematical notation, and the validity of statistical conclusions
- Self-directed and reliable when working independently on task-based assignments
- No prior AI training or annotation experience required
Nice to Have
- Experience with data annotation, data quality frameworks, or model evaluation systems
- Proficiency in production-level data science workflows — MLOps, CI/CD pipelines for models, or experiment tracking
- Familiarity with NLP techniques or transformer-based architectures
Why Join Us
- Work directly with industry-leading large language models at the frontier of AI development
- Fully remote and asynchronous — work when and where it suits you
- Freelance autonomy with meaningful, intellectually stimulating task-based work
- Contribute to AI systems that will influence how machine learning is applied across industries
- Potential for ongoing work and contract extension as new projects launch
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