Data Scientist | Remote

The Ai Training Company; France; Remote; EUR 65,000 - 90,000; Full time

Job summary

The Ai Training Company is 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.

We seek professionals who can work remotely, review statistical reasoning for correctness, assess ML approaches, and provide concise, technically sound written feedback.

Qualifications

• Professional experience in data science, quantitative analysis, statistics, or machine learning.
• Experience in experimentation, research, or related field.
• Ability to communicate technical ideas clearly in writing.

Responsibilities

• 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 and weak quantitative reasoning.
• Review experimental design and A/B testing methodology.
• Evaluate model selection, feature engineering, and validation approaches.
• Create expert prompts and realistic quantitative scenarios.
• Build or review datasets used for evaluation tasks.
• Develop reference solutions and expected answers.
• Check derivations, calculations, and interpretations.
• Identify data leakage, bias, and inappropriate metrics.
• Evaluate whether conclusions are supported by data.
• Apply structured evaluation rubrics consistently.
• Provide concise, technically sound written feedback.

Skills

Data science

Statistics

Machine learning

Experimentation

Python

R

SQL

Education

Advanced degree in Data Science, Statistics, Computer Science, Mathematics, Economics, OR, Physics, Engineering

Job description

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
• 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.