Remote Data Science & AI Benchmark Analyst

Weekday 1; United States; Remote; USD 109,000 - 164,000; Full time

Benefits offered by this job

Fully remote

Weekly payments

Job summary

Weekday 1 is seeking experienced Data Scientists and Quantitative Analysts to craft real-world analytics benchmarks for frontier AI models. You will design challenging data-analysis tasks, clean data, compare methods, and present actionable insights.

This fully remote, full-time role requires about 35 hours per week and collaboration with AI researchers. Candidates should have strong Python skills, experience with Jupyter/Colab, and a track record in data science or quantitative research.

Qualifications

• A master's degree, PhD, or equivalent practical experience in a quantitative STEM field.
• Minimum 1 year of professional experience in research, quantitative analysis, or data science.
• Strong data cleaning, exploratory data analysis, statistical testing, and interpretation of results.

Responsibilities

• Design realistic, multi-step data analysis challenges reflecting real research workflows.
• Create reproducible reference analyses using Jupyter Notebooks or Google Colab.
• Develop benchmark tasks with objective comparisons and statistical validation.
• Evaluate AI-generated analyses for correctness and interpretation quality.
• Identify analytical errors and reasoning gaps for expert audiences.
• Collaborate with AI researchers to improve benchmark quality and rigor.

Skills

Python

Data cleaning

Statistical analysis

Jupyter Notebooks

EDA

Education

Master's degree

PhD

Tools

Jupyter Notebooks

Google Colab

Pandas

NumPy

SciPy

scikit-learn

Git

Job description

Weekday 1 is seeking experienced Data Scientists and Quantitative Analysts to craft real-world analytics benchmarks for frontier AI models. You will design challenging data-analysis tasks, clean data, compare methods, and present actionable insights.

This fully remote, full-time role requires about 35 hours per week and collaboration with AI researchers. Candidates should have strong Python skills, experience with Jupyter/Colab, and a track record in data science or quantitative research.