Data Scientist (Masters)

About the Role

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

What You'll Do:

• 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 technical solutions including Python/R scripts, SQL queries, and mathematical derivations.
• Audit AI-Generated Code — Critically evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow.
• Expose Reasoning Failures — Identify and document logical flaws in AI reasoning (e.g., data leakage, overfitting, improper handling of imbalanced datasets) and provide structured feedback.

Who You Are:

• Currently pursuing or holding a Master's or PhD in Data Science, Statistics, Computer Science, or a quantitative field with a strong emphasis on data analysis.
• Deeply knowledgeable in core data science domains: supervised/unsupervised learning, deep learning, statistical inference, big data technologies (Spark, Hadoop), or NLP.
• A precise and analytical writer with the ability to explain complex algorithmic concepts and statistical results clearly.
• Naturally detail-oriented, capable of catching errors in code syntax, mathematical notation, and statistical logic.
• No prior AI or data annotation experience required.

Nice to Have:

• Prior experience with data annotation, data quality, or AI evaluation workflows.
• Proficiency in production-level data science practices like MLOps, CI/CD pipelines for models, or model monitoring.
• Familiarity with evaluation rubrics or quality assurance processes in technical contexts.