Data Science Expert - AI Content Specialist

Alignerr; United States; Remote; USD 83,000 - 131,000; Part time

Job summary

Alignerr Corp. is seeking a Data Science Expert – AI Content Specialist to stress-test and improve cutting-edge AI models.

This remote, hourly contractor role offers flexible scheduling (10–40 hours per week) and the opportunity to shape model reasoning with advanced ML and statistical methods. You will craft challenging data science problems, develop rigorous solutions in Python/R and SQL, and audit model outputs using PyTorch, TensorFlow, and Scikit-Learn.

Qualifications

• Master's or PhD in data science or related quantitative field
• Strong foundation in supervised/unsupervised learning, deep learning, NLP or big data technologies (Spark/Hadoop)
• Excellent written communication of complex algorithms and results
• High precision in code, math notation, and statistical reasoning

Responsibilities

• Design complex challenges spanning hyperparameter optimization and Bayesian inference
• Author ground-truth solutions with Python/R scripts, SQL queries, and derivations
• Audit AI-generated code for correctness, efficiency and quality across code, visualizations and stats
• Document and report on AI reasoning flaws and improvements

Skills

Written communication

Attention to detail

Stat/ML fundamentals

Education

Master's or PhD in Data Science/Statistics/CS

Tools

Python

R

SQL

Scikit-Learn

PyTorch

TensorFlow

Job description

Data Science Expert – AI Content Specialist

About The Role

What if your expertise in machine learning, statistics, and data engineering could directly shape how the world's most advanced AI systems think and reason? We're looking for Data Science Experts to stress-test, evaluate, and improve cutting-edge AI models - working remotely on your own schedule.

This is a high-impact contractor role where your deep domain knowledge becomes the benchmark that the next generation of AI is trained against.

• 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. Your problems become the proving ground for AI reasoning.
• Author Ground-Truth Solutions - Develop rigorous, step-by-step technical solutions - including Python/R scripts, SQL queries, and mathematical derivations - that serve as the gold standard for AI responses.
• Audit AI-Generated Code - Evaluate outputs from models using libraries like Scikit-Learn, PyTorch, and TensorFlow. Assess correctness, efficiency, and technical quality across code, visualizations, and statistical summaries.
• Sharpen AI Reasoning - Identify and document logical flaws in AI outputs - such as data leakage, overfitting, or improper handling of imbalanced datasets - and provide structured feedback that directly improves model intelligence.

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 one or more core areas: supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), or NLP
• Able to communicate complex algorithmic concepts and statistical results clearly and concisely in writing
• Highly precise - you catch errors in code syntax, mathematical notation, and statistical reasoning
• No prior AI experience required - your data science expertise is what matters

Nice to Have

• Experience with data annotation, data quality, or AI evaluation workflows
• Familiarity with production-level data science practices such as MLOps or CI/CD pipelines for models

Why Join Us

• Work directly with industry-leading AI language models at the frontier of AI research
• Fully remote and asynchronous - work when and where it suits you
• Flexible weekly commitment (10-40 hours) that fits around your existing schedule
• High-autonomy freelance work with meaningful, intellectually stimulating tasks
• Contribute to AI development that will influence how machine learning is understood and applied globally
• Potential for ongoing work and contract extension as new projects launch