Machine Learning Researcher (Remote | $245–$280/hr)

Synthires; California; Remote; USD 338,000 - 386,000; Part time

Job summary

Synthires is seeking an Applied Scientist for a fully remote contract role. You will apply Python, ML, and statistics to train and evaluate AI systems on a data-driven project.

You will design experiments, analyze results, and develop reproducible code and reports while collaborating with stakeholders to improve model performance and insights. The role emphasizes quantitative problem-solving, rigorous analytics, and clear technical communication.

Qualifications

• Proficiency in Python for data analysis and ML.
• Experience with Pandas and scikit-learn.
• Applied statistics, experimental design, and ML knowledge.

Responsibilities

• Design and conduct statistical analyses on complex data.
• Develop, validate, tune, and evaluate ML models.
• Apply data modeling and large-scale data transformations with Python.
• Collaborate with stakeholders on experimentation frameworks.
• Provide clear analytical reports and reproducible code.
• Review peer contributions and give constructive feedback.
• Create robust prompts, datasets, and reference solutions.
• Identify flawed methodologies and improve quantitative reasoning.

Skills

Python

Pandas

Scikit-learn

Applied statistics

Experiment design

Data modeling

Communication

Tools

scikit-learn

Job description

Applied Scientist

Position: Applied Scientist

Type: Contractor

Compensation: $245–$280/hour

Location: Remote

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.

Required Qualifications

• 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.

Preferred 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.