Data Scientist (Masters) — AI Data Trainer
What if your expertise in 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 Masters-level data scientists to challenge, evaluate, and improve cutting‐edge AI models — working hands‐on with the technology that's redefining the field.
This is a fully remote, flexible contract role. No prior AI industry experience required — just deep domain knowledge and a sharp analytical mind.
* Organization: Alignerr
* Type: Hourly Contract
* Location: Remote
* Commitment: 10–40 hours/week
What You'll Do
* Design Complex Challenges: Craft advanced data science problems spanning hyperparameter optimization, Bayesian inference, cross‐validation strategies, dimensionality reduction, and more — specifically designed to stress‐test AI reasoning.
* Author Ground‐Truth Solutions: Build 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 model outputs using libraries like Scikit‐Learn, PyTorch, and TensorFlow, assessing them for correctness, efficiency, and technical soundness.
* Sharpen Model Reasoning: Identify logical flaws in AI outputs — data leakage, overfitting, improper handling of imbalanced datasets — and deliver structured feedback that improves how models think.
* Work Independently: Complete task‐based assignments asynchronously on your own schedule.
Who You Are
* Pursuing or holding a Masters or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a strong emphasis on data analysis.
* Solid foundational knowledge across core areas — supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP.
* Able to communicate complex algorithmic and statistical concepts clearly and precisely in writing.
* Meticulous when reviewing code syntax, mathematical notation, and statistical conclusions.
* Self‐directed and reliable when working independently.
* No prior AI or data annotation experience required.
Nice to Have
* Experience with data annotation, data quality assurance, or evaluation systems.
* Familiarity with production‐level data science workflows — MLOps, CI/CD for models.
* Background in academic research or technical writing.
* Exposure to model interpretability, fairness, or robustness evaluation.
Why Join Us
* Work directly with industry‐leading large language models and cutting‐edge AI research.
* Fully remote and flexible — work when and where it suits you.
* Freelance autonomy with meaningful, intellectually stimulating work.
* Collaborate with top‐tier AI labs shaping the next generation of intelligent systems.
* Potential for ongoing work and contract extension as new projects launch.
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