Data Science Expert - AI Content Specialist

Job summary

Design advanced data science challenges and create rigorous, step-by-step solutions to benchmark AI model performance. Audit AI-generated code and reasoning, identify issues such as data leakage and overfitting, and provide structured feedback to improve model reliability.

Job details

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 Data Science Experts to stress-test, evaluate, and improve frontier AI models — identifying gaps in their reasoning and helping build smarter, more reliable systems. This is a fully remote, flexible contract role designed for data science professionals who want meaningful, intellectually stimulating work on their own terms. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Design Advanced Challenges — Craft sophisticated data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more to expose the limits of 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 authoritative benchmarks for AI evaluation. Audit AI-Generated Code — Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow, assessing correctness, efficiency, and best practices across data visualizations and statistical summaries. Refine Model Reasoning — Pinpoint logical failures such as data leakage, overfitting, and improper handling of imbalanced datasets, then deliver structured feedback that directly improves how AI models think. Who You Are Advanced degree (Master's or PhD — pursuing or completed) in Data Science, Statistics, Computer Science, or a related quantitative discipline Strong domain expertise in supervised/unsupervised learning, deep learning, big data technologies (Spark/Hadoop), NLP, or similar areas Clear technical communicator — able to explain complex algorithms and statistical results in precise, accessible written form Detail-oriented — rigorous when reviewing code syntax, mathematical notation, and the validity of statistical conclusions No prior AI industry experience required — your data science knowledge is what matters Nice to Have Experience with data annotation, data quality assessment, or evaluation systems Familiarity with production-level workflows such as MLOps or CI/CD for machine learning models Why Join Us Work directly with industry-leading AI models and top research labs at the frontier of AI development Fully remote and asynchronous — work when and where it suits you Freelance autonomy with the substance of high-impact, technically rigorous work Contribute to AI systems that will influence how millions of people interact with technology Strong potential for ongoing contract engagement as new projects launch

What you’ll do

Design advanced data science challenges and create rigorous, step-by-step solutions to benchmark AI model performance. Audit AI-generated code and reasoning, identify issues such as data leakage and overfitting, and provide structured feedback to improve model reliability.

Requirements

A pursuing or completed master's or PhD in data science, statistics, computer science, or a related quantitative field is required, along with strong expertise in relevant data science domains. Candidates should communicate technical concepts clearly and review code, mathematical notation, and statistical conclusions carefully; prior AI industry experience is not required.

Benefits

• Fully Remote Work
• Flexible Schedule
• Freelance Autonomy
• Potential for Ongoing Contract Engagement

Listed skills

• Machine learning · Preferred
• Python · Preferred
• SQL · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Data Science
• Machine Learning
• Statistics
• Data Engineering
• Hyperparameter Optimization
• Bayesian Inference
• Cross-Validation
• Dimensionality Reduction
• Python
• R
• SQL
• Scikit-Learn
• PyTorch
• TensorFlow
• Big Data Technologies
• Natural Language Processing

Job areas

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

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