Data Scientist

Responsibilities

• Evaluate AI-generated outputs across data science, statistics, machine learning, and quantitative reasoning problems.
• Create expert-level prompts and datasets designed to assess advanced quantitative capabilities.
• Develop accurate reference solutions for complex data science and statistical problems.
• Identify flawed methodologies, statistical errors, and weaknesses in quantitative reasoning.
• Assess the validity and quality of AI-generated analytical approaches.
• Review model outputs for technical accuracy, logical consistency, and sound statistical reasoning.
• Provide structured, actionable feedback to improve AI model performance.
• Apply strong quantitative judgment when evaluating experimental designs, analytical methods, and data-driven conclusions.
• Communicate technical findings and statistical concepts clearly and precisely.

Required Qualifications

• At least 1 year of professional experience at a top company in technology, finance, research, or a comparable environment.
• At least part of the qualifying professional experience must have been within the past 7 years.
• Strong expertise in data science, statistics, machine learning, or quantitative analysis.
• Undergraduate degree from a top-ranked university.
• Strong analytical and quantitative reasoning abilities.
• Ability to evaluate complex statistical and machine-learning methodologies.
• Clear written communication of technical and statistical concepts.
• Ability to identify subtle errors in quantitative reasoning and analytical approaches.
• Professional proficiency in English.

Preferred Qualifications

• Professional experience combining Python, machine learning, statistics, and data analysis.
• Experience with Pandas and other data science tools.
• Experience with experimentation and experimental design.
• Strong understanding of data modeling and quantitative methods.
• Experience developing analytical datasets or benchmark problems.
• Background in quantitative roles within technology, finance, or research organizations.
• Experience evaluating technical or AI-generated outputs.
• Strong ability to explain complex quantitative concepts clearly and concisely.