This is a fully remote position, open to applicants in United States.

📋 Description

• Engage with sophisticated language models on project-related scenarios and theoretical inquiries in data science.

• Validate the accuracy of facts and the logical integrity of model outputs.

• Record reproducible error traces.

• Propose enhancements to prompt engineering and evaluation criteria.

• Test language models in areas such as machine learning, statistical modeling, data engineering, data visualization, NLP, time series analysis, deep learning, and algorithm development.

• Document instances of model failures to enhance model reasoning.

⛳️ Requirements

• Expertise in data science fields including machine learning, statistical modeling, data engineering, data visualization, natural language processing, time series analysis, deep learning, and algorithm development.

• Proficiency in assessing supervised learning, unsupervised clustering, regression methods, model evaluation metrics, feature engineering, anomaly detection, and real-world data pipelines.

• Capability to document failure modes and capture reproducible error traces.

• Skill in verifying factual accuracy and logical integrity.

• Excellent metacognitive communication skills and the ability to “show your work.”

• A master’s or PhD in data science, computer science, statistics, or a closely related discipline is preferred.

• Peer-reviewed publications, industry experience, cloud platform familiarity, or contributions to open-source projects indicate a good match.

• Must have a secure computer and high-speed internet for contract work.