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Data Science Expert - AI Content Specialist

Offre en anglaisExpiré

Design complex data science challenges and author authoritative ground-truth solutions to train AI models. Audit AI-generated code and reasoning to identify logical flaws and improve model accuracy.

  • Télétravail
  • Montreal, Quebec, Canada
  • Publié 30 juill. 2026
  • Postuler avant le 29 août 2026
  • 1 poste

Ce poste est expiré

Ce poste chez Alignerr n’accepte plus de candidatures. L’offre originale reste disponible ci-dessous à titre de référence.

Expiré le 7 août 2026

Postes actuels chez Alignerr

Ces possibilités vérifiées acceptent toujours des candidatures.

Offre d’emploi originale

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 experienced data scientists to help train and evaluate cutting-edge AI models at Alignerr. You'll design complex technical challenges, author authoritative solutions, and audit AI-generated outputs — directly improving how these models handle real data science problems. This is a fully remote, flexible contract role built for working data scientists, researchers, and quantitative experts who want meaningful, intellectually stimulating work on their own schedule. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Design Complex Challenges: Craft rigorous, domain-spanning data science problems across areas like hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more Author Ground-Truth Solutions: Write step-by-step technical solutions — including Python/R scripts, SQL queries, and mathematical derivations — that serve as definitive reference answers for AI training Audit AI Outputs: Evaluate AI-generated code (using libraries like Scikit-Learn, PyTorch, and TensorFlow), data visualizations, and statistical summaries for correctness, efficiency, and best practices Sharpen AI Reasoning: Identify logical flaws in model reasoning — such as data leakage, overfitting, or improper handling of imbalanced datasets — and provide structured feedback that improves how AI models think through problems Who You Are Pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field Strong foundational knowledge in core areas such as supervised and unsupervised learning, deep learning, NLP, or big data technologies (Spark, Hadoop) Able to communicate complex algorithmic concepts and statistical results clearly and concisely in writing Highly precise when it comes to code syntax, mathematical notation, and statistical validity Self-directed and comfortable working independently on task-based assignments No prior AI or annotation experience required Nice to Have Experience with data annotation, data quality, or evaluation systems Familiarity with production-level data science workflows such as MLOps or CI/CD for models Background in academic research or technical writing Why Join Us Work directly with industry-leading language models on intellectually challenging problems Fully remote and asynchronous — work when and where it suits you Freelance autonomy with the structure of meaningful, well-defined tasks Contribute to AI development that advances the frontier of machine reasoning Potential for ongoing work and contract extension as new projects launch

Ce que vous ferez

Design complex data science challenges and author authoritative ground-truth solutions to train AI models. Audit AI-generated code and reasoning to identify logical flaws and improve model accuracy.

Exigences

Requires a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field. Must possess strong foundational knowledge in supervised/unsupervised learning and the ability to communicate complex algorithmic concepts clearly.

Avantages

• Freelance autonomy • Flexible schedule

Autres compétences pertinentes

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

  • Machine Learning
  • Statistics
  • Data Engineering
  • Python
  • R
  • SQL
  • Scikit-Learn
  • PyTorch
  • TensorFlow
  • Bayesian Inference
  • Hyperparameter Optimization
  • Dimensionality Reduction
  • NLP
  • Big Data
  • MLOps
  • Technical Writing

Domaines d’emploi

  • Data & Analytics
  • Technology
  • Science & Research
  • Software
  • Engineering

Renseignements supplémentaires

Formation minimale
Maîtrise
Expérience minimale
2+ ans
Postuler avant le
29 août 2026
Langue de l’offre
anglais
Heures de travail
40 heures par semaine
Exigences de lieu
Country, Montreal, Quebec, Canada
Niveau d’expérience
Mid-Senior level