Manager, Data Science, Outbound Communications

Key job responsibilities

• Optimize Outbound's inbox management and planning system to personalize frequency, send-time and relevance bar of our messages to customers.
• Design and execute large-scale experiments such as multi-arm elasticity tests or RCTs to measure and improve incrementality/performance of our models.
• Drive development of HVA propensity models (opt-out, purchase, etc.) to drive intended behavior of customers to their next stage of shopping and engagement with Amazon.
• Drive AI-based transformation in data accuracy and reporting: migrating and enhancing the self-serve analytics capabilities developed by the team, automating WBR preparation, building anomaly detection, etc.
• Own financial planning frameworks for outbound performance including QxG/HVE forecasting and ROI measurement for paid channel investments.
• Hire, develop, and mentor scientists and BIEs while partnering cross-functionally with engineering, product, marketing, and partner science teams (CBA, P13N, CFV) to productionize solutions at scale.
• Create, align and evolve your team's roadmap by prioritizing across multiple competing priorities using high judgement decisions.

Basic Qualifications

• 5+ years of building quantitative solutions as a scientist or science manager experience
• 2+ years of scientists or machine learning engineers management experience
• 5+ years of applying statistical models for large-scale application and building automated analytical systems experience
• Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
• Knowledge of Python or R or other scripting language

Preferred Qualifications

• Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
• Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems