Data Science Expert - AI Content Specialist

Job summary

Design advanced data science challenges and develop rigorous, step-by-step reference solutions using code and mathematical derivations. Evaluate AI-generated code and reasoning, identify errors such as data leakage and overfitting, and provide structured feedback to improve model performance.

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 work alongside leading AI research teams — designing rigorous challenges, authoring gold-standard solutions, and auditing AI-generated outputs to push model performance to its limits. This is a fully remote, flexible contract role built for experienced data scientists 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 advanced data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more — problems that genuinely stress-test 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 definitive reference answers Audit AI-Generated Code: Critically evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow — assessing correctness, efficiency, and best practices Refine Model Reasoning: Identify logical failures in AI responses — such as data leakage, overfitting, or improper handling of imbalanced datasets — and provide structured feedback that improves how models think Who You Are Hold or are pursuing a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field Strong foundational knowledge across core domains: 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 Highly detail-oriented — you catch errors in code syntax, mathematical notation, and statistical reasoning No prior AI training experience required — your domain expertise is what matters Nice to Have Experience with data annotation, data quality assurance, or AI evaluation workflows Familiarity with production-level data science practices such as MLOps or CI/CD pipelines for models Background in technical writing, research, or peer review Why Join Us Work directly on cutting-edge AI projects with world-leading research labs Fully remote and asynchronous — work when and where it suits you Freelance autonomy with the structure of meaningful, high-impact technical work Engage with state-of-the-art language models at a deeper level than almost any other role available Potential for ongoing work and contract extension as new projects launch

What you’ll do

Design advanced data science challenges and develop rigorous, step-by-step reference solutions using code and mathematical derivations. Evaluate AI-generated code and reasoning, identify errors such as data leakage and overfitting, and provide structured feedback to improve model performance.

Requirements

Applicants must hold or be pursuing a master's or PhD in data science, statistics, computer science, or a related quantitative field, and have strong knowledge of core data science domains. They must communicate technical concepts clearly in writing and demonstrate close attention to detail; prior AI training experience is not required.

Benefits

• Flexible Schedule
• Remote Work
• Freelance Autonomy
• Potential for Ongoing Work and Contract Extension

Listed skills

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