Data Scientist | Remote

Data Scientists, Quantitative Analysts & ML/Experimentation Experts. Remote AI Project
We are seeking experienced Data Scientists, Quantitative Analysts, Machine Learning Scientists, Experimentation Experts, Product Data Scientists, and Research Professionals to contribute to an advanced AI evaluation project focused on statistics, machine learning, experimentation, and quantitative reasoning.
What You’ll Do
Evaluate AI-generated responses to data science and quantitative problems
Review statistical reasoning for correctness and methodological rigor
Assess machine learning approaches and modeling decisions
Identify flawed assumptions, invalid methods, and weak quantitative reasoning
Review experimental design and A/B testing methodology
Evaluate model selection, feature engineering, and validation approaches
Create expert-level prompts and realistic quantitative scenarios
Build or review datasets used for evaluation tasks
Develop high-quality reference solutions and expected answers
Check mathematical derivations, calculations, and interpretations
Identify data leakage, selection bias, confounding, and inappropriate metrics
Evaluate whether conclusions are supported by the underlying data
Apply structured evaluation rubrics consistently
Provide concise, technically sound written feedback
Who Can Apply
Relevant backgrounds include:
Data Scientists, Senior Data Scientists, Staff Data Scientists, Principal Data Scientists, Lead Data Scientists, Applied Data Scientists, Research Data Scientists, and Decision Scientists.
Quantitative backgrounds may include:
Quantitative Analysts, Quant Researchers, Quantitative Researchers, Quantitative Scientists, Quantitative Strategists, Statistical Analysts, Mathematical Modelers, and Quantitative Consultants.
Machine learning backgrounds may include:
Machine Learning Scientists, Applied Scientists, ML Researchers, Research Scientists, AI Researchers, Machine Learning Engineers with strong statistical expertise, and Applied ML Professionals.
Product and experimentation backgrounds may include:
Product Data Scientists, Experimentation Scientists, Growth Data Scientists, Decision Scientists, Product Analysts, Growth Analysts, Experimentation Analysts, Causal Inference Scientists, and Measurement Scientists.
Analytics backgrounds may include:
Senior Data Analysts, Analytics Scientists, Business Data Scientists, Statistical Analysts, Advanced Analytics Professionals, BI Analysts with strong statistical backgrounds, and Analytics Engineers with substantial modeling experience.
Research backgrounds may include:
Research Scientists, Economists, Econometricians, Operations Researchers, Computational Scientists, Biostatisticians, Statisticians, Social Science Researchers, and Academic Researchers with strong quantitative expertise.
Finance backgrounds may include:
Quantitative Finance Professionals, Risk Modelers, Financial Data Scientists, Portfolio Analysts, Pricing Analysts, Credit Risk Analysts, Market Risk Analysts, and Financial Researchers with strong statistics or machine learning experience.
Requirements
Professional experience in data science, quantitative analysis, statistics, machine learning, experimentation, research, or a closely related field
At least 1 year of experience at a top-tier company, research organization, financial institution, or comparable high-performing environment
At least part of that experience must have occurred within the past 7 years
Currently based in an English-speaking country
Strong understanding of statistics and quantitative reasoning
Ability to identify methodological and analytical errors
Ability to communicate technical ideas clearly in writing
Strong attention to detail
Comfortable evaluating unfamiliar quantitative problems
Ability to work independently in a remote environment
Preferred Background
Experience at a leading technology company, financial institution, research organization, or quantitative firm
Advanced degree in Data Science, Statistics, Computer Science, Mathematics, Economics, Operations Research, Physics, Engineering, or a related quantitative field
Experience with experimentation or causal inference
Experience building production machine learning models
Experience conducting product or growth analytics
Experience with quantitative research
Experience reviewing other analysts’ or scientists’ work
Experience writing technical documentation or research
Strong Python, R, or SQL skills
This opportunity is ideal for quantitative professionals who can look at a statistical or machine learning solution and quickly determine whether the methodology is valid, where the reasoning breaks down, whether the conclusions are justified, and how the analysis should be improved. We are a referral partner of the client.

Work arrangement
Yes