Data Science Expert – AI Content Specialist

Data Science Expert — AI Content Specialist 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 think and reason?

We’re looking for experienced data scientists to join Alignerr’s network of subject matter experts — working alongside leading AI research labs to stress-test, challenge, and improve cutting‑edge language models. Your expertise becomes the benchmark these models are measured against.

This is a fully remote, flexible contract role built for professionals who want high‑impact work on their own schedule.

• Organization:
  Alignerr
• Type:
  Hourly Contract
• Location:
  
  Remote
• Commitment: 10–40 hours/week

• 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 reference solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the gold standard for model evaluation
• Audit AI‑Generated Code — Evaluate AI outputs using libraries like Scikit‑Learn, PyTorch, and Tensor Flow for technical accuracy, efficiency, and best practices
• Identify Reasoning Failures — Spot logical flaws in AI reasoning — data leakage, overfitting, mishandled class imbalances — and provide structured feedback that directly improves model performance
• Work Independently — Complete task‑based assignments asynchronously on a schedule that works for you

• Formally trained — Master’s (pursuing or completed) or PhD in Data Science, Statistics, Computer Science, or a quantitative field with heavy emphasis on data analysis
• Domain‑deep — Strong foundational knowledge across supervised/unsupervised learning, deep learning, NLP, or big data technologies (Spark, Hadoop)
• Analytically articulate — Able to explain complex algorithmic concepts and statistical results clearly in writing
• Precision‑oriented — High attention to detail when reviewing code syntax, mathematical notation, and statistical conclusions
• No prior AI experience required — Your subject matter expertise is what matters

• Experience with data annotation, data quality, or model evaluation workflows
• Familiarity with production‑level data science practices such as MLOps or CI/CD for models
• Background in technical writing or academic publishing

• Work directly with industry‑leading AI research labs on projects that push the frontier of what AI can do
• Fully remote and asynchronous — work from anywhere, on your own schedule
• Freelance autonomy with consistently meaningful, intellectually stimulating work
• Ongoing contract opportunities as new AI projects launch
• Contribute to AI development that has a real and lasting impact on how these systems reason about data science