Senior Data Scientist
$98
Data scientists play a critical role in AI training. These roles involve evaluating statistical analysis, assessing data modeling approaches, reviewing visualization choices, and validating predictive modeling. You will help AI understand hypothesis testing, regression, classification, and data-driven decision making. Ideal for data scientists, statisticians, and analytics professionals. Pay: $50-$110/hr.
Part of: Coding & Software Engineering
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Data science evaluation combines statistical rigor with practical analysis skills. You'll review AI-generated analytical approaches and assess whether they're statistically validβdoes this regression account for multicollinearity? Is this A/B test properly powered? Does this correlation claim establish causation? Tasks often provide a dataset scenario and ask you to evaluate whether the AI's chosen method (e.g., logistic regression vs. random forest) is appropriate and whether conclusions drawn from the analysis are defensible. SQL query evaluation is common: you'll check for correctness, performance, and whether window functions are used appropriately. Proficiency in Python (pandas, scikit-learn, statsmodels) and SQL is expected.
Strong foundation in statistics, Python (pandas, numpy, scikit-learn), SQL, and data visualization. Experience with A/B testing, regression analysis, and feature engineering is valuable.
Not always. Bachelor's + 3+ years professional data science experience qualifies for many roles. Master's or PhD in statistics, data science, or related field unlocks higher-paying opportunities ($80-110/hr).
Data science roles focus on statistical analysis, business insights, and data exploration. ML engineering focuses on model training and deployment. Some overlap exists, but data science emphasizes analysis over engineering.
Entry-level data scientists: $50-70/hr. Senior data scientists: $70-90/hr. PhD statisticians: $90-110/hr. Kaggle competition winners and specialized experts may earn more.
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