Applied Scientist

Applied Scientist

Role Overview

• Job Type: Contract

• Work Arrangement: Remote

• Compensation: $470,400–$537,600 per year (annualized equivalent)

• Hourly Rate: $245–$280

About the Role

We are seeking experienced Applied Scientists to contribute expertise in statistical analysis, machine learning, experimentation, and quantitative problem-solving. You will develop and evaluate analytical solutions, produce reproducible code, and assess AI-generated outputs for technical accuracy and sound reasoning.

The role combines applied data science with AI model evaluation. You will create expert-level prompts, datasets, and reference solutions, identify methodological weaknesses, and provide structured feedback to improve model performance.

This opportunity is suited to professionals with strong Python skills, applied statistics expertise, and practical experience developing and evaluating machine learning models. Previous AI experience is not required.

Key Responsibilities

• Design and execute statistical analyses to uncover actionable insights from complex datasets.

• Develop, validate, tune, and evaluate machine learning models for business or research objectives.

• Use Python and Pandas to transform, analyze, and model structured and unstructured data.

• Design experimentation frameworks with stakeholders and analyze experimental outcomes.

• Evaluate AI-generated outputs involving statistics, machine learning, experimentation, and quantitative problems.

• Create expert-level prompts, datasets, and reference solutions for model evaluation.

• Identify flawed methodologies, statistical errors, and weaknesses in quantitative reasoning.

• Produce reproducible code, analytical reports, and clear technical documentation.

• Review peer contributions and provide constructive feedback to support quality and knowledge sharing.

• Document methodologies, findings, and recommendations with precision.

Required Qualifications

• Strong Python programming skills, including proficiency with Pandas and familiarity with scikit-learn.

• Demonstrated expertise in applied statistics, experimental design, and machine learning.

• Experience developing, tuning, validating, and evaluating machine learning models.

• Strong data modeling skills and experience managing data transformations.

• Ability to identify statistical errors, methodological flaws, and weaknesses in analytical reasoning.

• Excellent written and verbal communication skills.

• Ability to produce reproducible code and well-organized technical reports.

Preferred Qualifications

• At least one year of experience at a leading technology, finance, or research company.

• Advanced academic training or practical experience in data science, applied mathematics, or a related field.

• Experience working on cross-functional or collaborative data science projects.

• Strong technical documentation and analytical review skills.

Key Skills

Applied science, Python, machine learning, applied statistics, data analysis, experimentation, experimental design, Pandas, scikit-learn, data modeling, statistical inference, model evaluation, quantitative reasoning, data transformation, reproducible research, analytical reporting, and technical communication.

Compensation

The hourly rate is $245–$280, equivalent to approximately $470,400–$537,600 per year at 1,920 working hours annually. This annualized figure is for comparison only; actual earnings depend on contracted hours and workload.

What to Expect

You will combine applied scientific analysis with technical evaluation of AI outputs. Typical deliverables include statistical analyses, machine learning solutions, reproducible code, expert reference datasets, and structured feedback on quantitative reasoning. The work emphasizes methodological rigor, analytical accuracy, and clear technical communication. Previous AI experience is not required.