AI Research Scientist

About the Opportunity

We are seeking skilled Applied Scientists to contribute to a data-driven project focused on advanced analytics, statistical analysis, and experimentation. In this role, you will apply your expertise in Python, machine learning, and applied statistics to help train and evaluate next-generation AI systems. Your work will help improve how AI models learn, reason, and perform by providing high-quality, real-world expertise. The opportunity emphasizes quantitative problem-solving, experimentation, and clear technical communication. Prior AI experience is not required; relevant domain expertise is what matters.

Key Responsibilities

• Design and conduct statistical analyses to uncover actionable insights from complex datasets.
• Develop, validate, tune, and evaluate machine learning models for business and research objectives.
• Apply data modeling techniques and manage large-scale data transformations using Python and Pandas.
• Collaborate with stakeholders to establish experimentation frameworks and analyze results.
• Document methodologies, findings, and recommendations through clear, precise analytical reports.
• Review peer contributions and provide constructive, high-quality feedback.
• Deliver reproducible code and well-organized analytical reports.
• Evaluate AI-generated 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 and capabilities.

Requirements & Tech Stack

• Proficiency in Python for data analysis, statistical computing, and machine learning.
• Experience with Pandas and familiarity with machine learning libraries such as scikit-learn.
• Demonstrated knowledge of applied statistics, experimental design, and machine learning.
• Experience developing, tuning, and evaluating machine learning models in practical settings.
• Strong data modeling skills and experience working with structured and unstructured data.
• Excellent written and verbal communication skills.
• Ability to produce reproducible code, precise technical documentation, and clear analytical reports.

Qualifications

• At least one year of experience at a leading company in technology, finance, or research.
• An advanced academic background or hands-on experience in data science, applied mathematics, statistics, or a related field.
• Experience collaborating on open or cross-functional data science projects.
• Strong analytical judgment and the ability to assess complex quantitative problems.

Compensation & Engagement

• Compensation: $245–$280 per hour.
• Engagement Type: Contractor.
• Work Arrangement: Fully remote.
• Project Focus: Applied science, advanced analytics, machine learning, statistical analysis, and experimentation.