Machine Learning Scientist (Remote | $150-$350/hr) in Fremont

You will work on expert-level data science problems, assess AI-generated solutions, identify methodological and statistical weaknesses, and provide structured feedback that helps models reason more accurately and effectively.

• At least 1 year of professional experience at a top company in technology, finance, research, or a comparable environment. \n

• At least part of the qualifying professional experience must have been within the past 7 years. \n

• Strong expertise in data science, statistics, machine learning, or quantitative analysis. \n

• Undergraduate degree from a top-ranked university. \n

• Strong analytical and quantitative reasoning abilities. \n

• Ability to evaluate complex statistical and machine-learning methodologies. \n

• Clear written communication of technical and statistical concepts. \n

• Ability to identify subtle errors in quantitative reasoning and analytical approaches. \n

• Professional proficiency in English. \n, * Professional experience combining Python, machine learning, statistics, and data analysis., * Candidates should have at least 1 year of experience working at a top company in technology, finance, research, or a related field.

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• Evaluate AI-generated outputs across data science, statistics, machine learning, and quantitative reasoning problems. \n

• Create expert-level prompts and datasets designed to assess advanced quantitative capabilities. \n

• Develop accurate reference solutions for complex data science and statistical problems. \n

• Identify flawed methodologies, statistical errors, and weaknesses in quantitative reasoning. \n

• Assess the validity and quality of AI-generated analytical approaches. \n

• Review model outputs for technical accuracy, logical consistency, and sound statistical reasoning. \n

• Provide structured, actionable feedback to improve AI model performance. \n

• Apply strong quantitative judgment when evaluating experimental designs, analytical methods, and data-driven conclusions. \n

• Communicate technical findings and statistical concepts clearly and precisely. \n

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