Data Scientist | Remote

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.

• 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.