Data Science Expert - AI Content Specialist
Alignerr, Chicago, IL, United States
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 next generation of AI thinks and reasons? We're looking for Data Science Experts to help train and refine cutting-edge AI models - working alongside world-leading AI research labs from wherever you are in the world.
This is a fully remote, flexible contract role designed for experienced data scientists, ML engineers, and quantitative researchers who want to do 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 Advanced Challenges
- Develop complex, expert-level data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
Author Ground-Truth Solutions
- Write rigorous, step-by-step technical solutions - including Python/R scripts, SQL queries, and mathematical derivations - that serve as the gold standard for model training
Audit AI-Generated Code
- Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for technical correctness, efficiency, and best practices
Refine AI Reasoning
- Identify logical failures in AI thinking - such as data leakage, overfitting, or mishandled class imbalance - and deliver structured feedback that improves model performance
Stress-Test Model Limits
- Push AI systems to their boundaries across machine learning theory, statistical inference, neural network architectures, and data engineering pipelines
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 expertise in 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 attention to detail - from code syntax to mathematical notation to the validity of statistical conclusions
Self-directed and comfortable working independently on technical tasks
No prior AI or annotation experience required
Nice to Have Experience with data annotation, data quality, or AI evaluation workflows
Familiarity with production data science practices such as MLOps or CI/CD pipelines for models
Prior work in academic research, technical writing, or quantitative analysis
Why Join Us Work directly with industry-leading large language models and cutting-edge AI research
Fully remote and async - work on your own schedule, from anywhere
Freelance autonomy with consistent, meaningful technical work
Engage with intellectually challenging problems that have a real impact on the future of AI
Potential for ongoing contract renewals as new projects launch
About the Role
What if your deep knowledge of machine learning, statistics, and data engineering could directly shape how the next generation of AI thinks and reasons? We're looking for Data Science Experts to help train and refine cutting-edge AI models - working alongside world-leading AI research labs from wherever you are in the world.
This is a fully remote, flexible contract role designed for experienced data scientists, ML engineers, and quantitative researchers who want to do 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 Advanced Challenges
- Develop complex, expert-level data science problems spanning hyperparameter optimization, Bayesian inference, cross-validation strategies, dimensionality reduction, and more
Author Ground-Truth Solutions
- Write rigorous, step-by-step technical solutions - including Python/R scripts, SQL queries, and mathematical derivations - that serve as the gold standard for model training
Audit AI-Generated Code
- Evaluate AI outputs using libraries like Scikit-Learn, PyTorch, and TensorFlow for technical correctness, efficiency, and best practices
Refine AI Reasoning
- Identify logical failures in AI thinking - such as data leakage, overfitting, or mishandled class imbalance - and deliver structured feedback that improves model performance
Stress-Test Model Limits
- Push AI systems to their boundaries across machine learning theory, statistical inference, neural network architectures, and data engineering pipelines
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 expertise in 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 attention to detail - from code syntax to mathematical notation to the validity of statistical conclusions
Self-directed and comfortable working independently on technical tasks
No prior AI or annotation experience required
Nice to Have Experience with data annotation, data quality, or AI evaluation workflows
Familiarity with production data science practices such as MLOps or CI/CD pipelines for models
Prior work in academic research, technical writing, or quantitative analysis
Why Join Us Work directly with industry-leading large language models and cutting-edge AI research
Fully remote and async - work on your own schedule, from anywhere
Freelance autonomy with consistent, meaningful technical work
Engage with intellectually challenging problems that have a real impact on the future of AI
Potential for ongoing contract renewals as new projects launch