Staff Data Scientist, Catalog
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The role
Lead the transition from descriptive reporting to predictive modeling, causal inference, and robust experimentation for catalog data.
Develop and deploy ML models for catalog health scoring, anomaly detection, and data quality prediction across millions of SKUs.
Apply advanced techniques such as transformers, foundation models, and Bayesian inference to improve data accuracy and completeness.
Design scientific frameworks and metrics to monitor catalog health and proactively detect emerging data issues.
Automate repetitive catalog management processes using data science, ML, and LLMs to reduce manual errors.
Collaborate with engineering, product, and business leaders to ensure measurable impact and strengthen the team’s scientific capabilities.
Develop and deploy ML models for catalog health scoring, anomaly detection, and data quality prediction across millions of SKUs.
Apply advanced techniques such as transformers, foundation models, and Bayesian inference to improve data accuracy and completeness.
Design scientific frameworks and metrics to monitor catalog health and proactively detect emerging data issues.
Automate repetitive catalog management processes using data science, ML, and LLMs to reduce manual errors.
Collaborate with engineering, product, and business leaders to ensure measurable impact and strengthen the team’s scientific capabilities.
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