Data Scientist (Masters) — AI Data Trainer
About The Role
What if your expertise in machine learning, statistical inference, and data engineering could directly shape how the world's most advanced AI models think and reason? We're looking for Masters-level data scientists to challenge, stress-test, and refine cutting-edge AI systems — helping ensure they reason correctly, write clean code, and handle complex problems with precision.

Organization: Alignerr

Type: Hourly Contract

Location: Remote

Commitment: 10–40 hours/week

What You'll Do

Design complex data science challenges across domains like hyperparameter optimization, Bayesian inference, cross-validation strategies, and dimensionality reduction — pushing AI models to their limits

Author rigorous ground-truth solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the gold standard for model evaluation

Audit AI-generated code and outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow — assessing technical accuracy, efficiency, and correctness

Identify and document reasoning failures such as data leakage, overfitting, and improper handling of imbalanced datasets, then provide structured feedback to sharpen model reasoning

Work independently and asynchronously — fully on your own schedule

Who You Are

Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science,



or a quantitative field with a solid emphasis on data analysis

Deeply knowledgeable in core areas such as supervised and unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP

Able to write clearly and precisely about complex algorithmic concepts and statistical results for technical audiences

Naturally detail-oriented — you catch errors in code syntax, mathematical notation, and statistical reasoning that others miss

Self-motivated and consistent when working independently

No prior AI or data annotation experience required

Nice to Have

Experience with data annotation, data quality evaluation, or AI evaluation systems

Proficiency in production-level data science workflows such as MLOps or CI/CD for models

Familiarity with model benchmarking or technical content authoring

Background spanning multiple data science subfields — the broader your expertise, the more impactful your contributions

Why Join Us

Work directly with industry-leading AI research labs on cutting-edge model development

Fully remote and flexible — work when and where it suits you

Freelance autonomy with the structure of meaningful, task-based work

Make a direct, tangible impact on how advanced AI models reason about data science

Potential for ongoing work and contract extension as new projects launch

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📌 Data Scientist (Masters) (Quebec City)
🏢 Alignerr
📍 Quebec City