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 problemsReview statistical reasoning for correctness and methodological rigorAssess machine learning approaches and modeling decisionsIdentify flawed assumptions, invalid methods, and weak quantitative reasoningReview experimental design and A/B testing methodologyEvaluate model selection, feature engineering, and validation approachesCreate expert-level prompts and realistic quantitative scenariosBuild or review datasets used for evaluation tasksDevelop high-quality reference solutions and expected answersCheck mathematical derivations, calculations, and interpretationsIdentify data leakage, selection bias, confounding, and inappropriate metricsEvaluate whether conclusions are supported by the underlying dataApply structured evaluation rubrics consistentlyProvide 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 fieldAt least 1 year of experience at a top-tier company, research organization, financial institution, or comparable high-performing environmentAt least part of that experience must have occurred within the past 7 yearsCurrently based in an English-speaking countryStrong understanding of statistics and quantitative reasoningAbility to identify methodological and analytical errorsAbility to communicate technical ideas clearly in writingStrong attention to detailComfortable evaluating unfamiliar quantitative problemsAbility to work independently in a remote environment Preferred Background Experience at a leading technology company, financial institution, research organization, or quantitative firmAdvanced degree in Data Science, Statistics, Computer Science, Mathematics, Economics, Operations Research, Physics, Engineering, or a related quantitative fieldExperience with experimentation or causal inferenceExperience building production machine learning modelsExperience conducting product or growth analyticsExperience with quantitative researchExperience reviewing other analysts’ or scientists’ workExperience writing technical documentation or researchStrong 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.