Data Scientist; Masters

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

• 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 Tensor Flow, 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

• 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

• 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

• 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