Lead Advanced Analytics, Guest Product

Responsibilities

• Work with large and complex data sets to solve challenging problems using different analytical and statistical approaches.
• Apply technical expertise with quantitative analysis, experimentation, data mining, forecasting and the presentation of data to identify trends and patterns that can inform decision-making.
• Collaborate closely with Product, Engineering, Finance, Marketing, Operations, Data Science, Advanced Analytics, Data and Analytical Engineering, Capacity Planning and other cross-functional teams to provide actionable insights.
• Design, execute, and analyze experiments to measure feature impact and guide product iterations. Leverage causal methods when traditional randomized trials aren’t available.
• Design and build metrics / dimensions to monitor product and business performance.
• Build sophisticated reporting and analytical tools that empower stakeholders to make data-driven decisions.
• Present findings and recommendations to stakeholders, including senior leadership, in a clear and concise manner.
• Stay up-to-date with the latest industry trends and advancements in quantitative and qualitative data analysis techniques.
• Leverage AI to automate repetitive tasks and empower stakeholders.

Requirements

• 6+ years of industry experience with a degree (Masters or PhD is a plus) in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research).
• Prior experience in an advanced analytics or product data science role.
• Exceptional business acumen, strategic thinking skills, and the ability to conduct rigorous analysis and make informed judgments.
• Excellent communication skills, capable of engaging with a variety of stakeholders and conveying complex concepts in an accessible manner.
• Proven stakeholder management skills, with the ability to collaborate and influence across functions.
• Experience partnering with product teams to drive action and providing expertise and direction on analytics, data science, experimental design, and measurement.
• Experience in analysis of A|B experiments and statistical data analysis.
• Experience designing and building metrics, from conception to building prototypes with data pipelines.
• Strong expertise in at least one programming language (Python or R) and SQL.
• Experience with AI-assisted analytics (Claude, ChatGPT, etc).
• An agile, growth-minded approach, demonstrated through a history of driving projects from ideation to impact.