ML Research Scientist (Remote | $245–$280/hr)

Synthires; United States; Remote; USD 338,000 - 386,000; Full time

Job summary

Synthires is seeking an Applied Scientist on a remote contractor basis to advance analytics, experimentation, and ML for next‑gen AI systems. You will design analyses, build and evaluate models, and prepare reproducible reports while collaborating with stakeholders.

The role emphasizes strong Python/Pandas skills, data modeling, and clear communication, with the flexibility of remote work and an hourly compensation model.

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.

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.

Skills

Python

Data analysis

Statistics

Machine learning

Pandas

Scikit-learn

Communication

Quantitative reasoning

Problem solving

Tools

Pandas

Scikit-learn

Job description

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.