AI Research Scientist; Remote

Applied Scientist (Remote | $245–$280/hr)

Position: Applied Scientist

Type: Contractor

Compensation: $245–$280 per hour

Location: Remote

About the Opportunity

An AI-focused project is seeking Applied Scientists to contribute expertise in advanced analytics, experimentation, statistics, and machine learning. Contractors will help improve next-generation AI systems by evaluating model outputs, developing high-quality datasets, and providing expert feedback. Prior AI experience is not required.

Key Responsibilities

• Design and execute statistical analyses to uncover insights from complex datasets.
• Develop, validate, and evaluate machine learning models for business and research objectives.
• Apply data modeling techniques and manage data transformations using Python and Pandas.
• Collaborate with stakeholders to establish experimentation frameworks and analyze outcomes.
• Document methodologies, findings, and recommendations clearly and accurately.
• Review peer contributions and provide constructive technical feedback.
• Deliver reproducible code and organized analytical reports.
• Evaluate AI model outputs involving statistics, machine learning, experimentation, and quantitative reasoning.
• Create expert-level prompts, datasets, and reference solutions.
• Identify flawed methodologies, statistical errors, and weaknesses in quantitative reasoning.
• Provide structured feedback to improve AI model performance.

Required Qualifications

• Strong proficiency in Python and data analysis.
• Knowledge of machine learning, statistics, experimentation, and data modeling.
• Experience with Pandas and related data science tools.
• Strong analytical, problem-solving, and quantitative reasoning skills.
• Excellent written and verbal communication skills.

Preferred Qualifications

• At least one year of experience at a leading company in technology, finance, or research.
• Proficiency with Python libraries such as Pandas and scikit-learn.
• Demonstrated experience in applied statistics, experimental design, and machine learning.
• Experience developing, tuning, and evaluating machine learning models.
• Ability to work with structured and unstructured data.
• Experience collaborating on cross-functional or open data science projects.
• Advanced academic background or practical experience in data science, applied mathematics, or a related field.

Compensation

• Hourly compensation of $245–$280.

Application Process

The application process was not specified in the provided listing.