Machine Learning Scientist (Remote | $245-$280/hr)

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

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Position: Applied Scientist

Type: Contractor

Compensation: $245–$280/hour

Location: Remote

About the Opportunity

This opportunity is for experienced Applied Scientists to contribute to advanced analytics, experimentation, and AI model evaluation. You'll develop statistical analyses and machine learning solutions while helping train next-generation AI systems. No prior AI experience is required.

Key Responsibilities

• Design statistical analyses and experiments to uncover actionable insights.
• Develop, validate, and evaluate machine learning models.
• Use Python and Pandas for data modeling and large-scale data transformations.
• Evaluate AI outputs and identify statistical errors or flawed quantitative reasoning.
• Create expert-level prompts, datasets, and reference solutions.
• Deliver reproducible code, analytical reports, and clear technical documentation.
• Review peer contributions and provide constructive feedback.

Required Qualifications

• Strong proficiency in Python, particularly Pandas and related data science libraries.
• Experience in applied statistics, experimentation, data analysis, and machine learning.
• Ability to develop, tune, and evaluate machine learning models.
• Strong quantitative reasoning and data modeling skills.
• Excellent written and verbal communication skills.

Preferred Qualifications

• At least one year of experience at a leading technology, finance, or research company.
• Experience with scikit-learn and structured or unstructured data.
• Advanced academic background or practical experience in data science, applied mathematics, or a related field.
• Experience with cross-functional or collaborative data science projects.

Compensation

• $245–$280/hour.
• Remote contractor opportunity.
• 100 openings listed.

Application Process

1. Submit an updated resume highlighting relevant data science and machine learning experience.
2. Complete the required screening or assessment steps.
3. Proceed with further evaluation and onboarding if selected. xhyhwjd

Remote working/work at home options are available for this role.