Data Science Expert - AI Content Specialist
Job in
Washington, District of Columbia, 20022, USA
Listed on 2026-08-28
Listing for:
Alignerr
Full Time
position Listed on 2026-08-28
Job specializations:
-
IT/Tech
AI Engineer (Applied/Software), Data Scientist, Machine Learning/ ML Engineer, Data Analyst
Job Description & How to Apply Below
Data Science Expert – AI Content Specialist About The Role
- Organization:
Alignerr - Type:
Hourly Contract - Location:
Remote - Commitment: 10-40 hours/week
- Design Advanced Challenges
- Create rigorous data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more - Author Ground-Truth Solutions
- Develop step-by-step expert solutions including Python/R scripts, SQL queries, and mathematical derivations that serve as the definitive benchmark for AI responses - Audit AI-Generated Code
- Evaluate code written using libraries like Scikit-Learn, PyTorch, and Tensor Flow for correctness, efficiency, and best practices - Refine AI Reasoning
- Identify flaws in AI logic - such as data leakage, overfitting, or mishandled class imbalance - and provide structured feedback that improves model reasoning at a fundamental level - Document Failure Modes
- Surface and record how AI models break down on complex technical topics so research teams can harden model performance
- Holds or is pursuing a Master's or PhD in Data Science, Statistics, Computer Science, or a related quantitative field
- Strong foundational knowledge across 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 conclusions that others miss
- Self-motivated and reliable when working independently on task-based assignments
- No prior AI or annotation experience required
- Experience with data annotation, data quality assurance, or evaluation systems
- Familiarity with production-level data science workflows - MLOps, CI/CD pipelines for models, or model monitoring
- Prior work auditing or benchmarking machine learning systems
- Work directly with industry-leading AI research labs on cutting-edge model development
- Fully remote and asynchronous - work when and where it suits you
- Freelance autonomy with consistent, intellectually rewarding task-based work
- Contribute to AI that will influence how advanced models reason about data science for years to come
- Potential for ongoing work and contract extension as new projects launch
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