Data Scientist, Analytics (Technical Leadership) Responsibilities:

• Work with complex data sets to solve challenging problems using analytical and statistical approaches
• Apply technical expertise in quantitative analysis, experimentation, and data mining to develop product strategies
• Identify and measure success through goal setting, forecasting, and monitoring key metrics
• Partner with cross-functional teams to inform and execute product strategy and investment decisions
• Build long-term vision and strategy for programs and products
• Collaborate with executives to define and develop data platforms and instrumentation
• Effectively communicate insights and recommendations to stakeholders
• Define success metrics, forecast changes, and set team goals
• Support developing roadmaps and coordinate analytics efforts across teams

Minimum Qualifications:

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Mathematics, Statistics, Operations Research) 5+ years of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, Matlab)
• 8+ years of work experience leading analytics work in IC capacity, working collaboratively with Engineering and cross-functional partners, and guiding data-influenced product planning, prioritization and strategy development
• Experience working effectively with and leading complex analytics projects across multiple stakeholders and cross-functional teams, including Engineering, PM/TPM, Analytics and Finance
• Experience with predictive modeling, machine learning, and experimentation/causal inference methods
• Experience communicating complex technical topics in a clear, precise, and actionable manner

Preferred Qualifications:

• 10+ years of experience communicating the results of analyses to leadership teams to influence the strategy
• Masters or Ph.D. Degree in a quantitative field
• Bachelor's Degree in an analytical or scientific field (e.g. Computer Science, Engineering, Mathematics, Statistics, Operations Research)
• 10+ years of experience doing complex quantitative analysis in product analytics
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

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