Advanced Analytics Lead, Competitive Insights

Role Overview

• Define metrics and dimensions in partnership with cross-functional stakeholders, focused on competitive pricing and insights.
• Build and maintain metrics pipelines, coding new metrics into automated pipelines using internal data infrastructure.
• Onboard new metrics into the team's pipeline tooling, working independently to learn and apply new internal systems and skills as needed.
• Generate interactive dashboards and analyses using AI tooling (e.g., Claude) to accelerate delivery.
• Translate analytical findings into clear narratives and slide presentations for senior partners.
• Share competitive insights internally and, where appropriate, surface insights for hosts.

Requirements

• Strong SQL (must-have): Expert-level SQL ability.
• Hands-on experience with metrics pipeline development: building metrics and dimensions, and coding them into automated pipelines.
• Familiarity with large metric pipeline infrastructures and the ability to integrate with internal data pipeline tooling.
• Proficiency in at least one programming language beyond SQL. The specific language is flexible (Python, R, or others);
• Contextual familiarity with A/B testing and statistical data analysis. This will not be heavily tested in interviews, but awareness is needed because experimentation is part of the broader team's work.
• AI tools (must-have): Comfort using Claude or other AI tools as a regular part of the workflow.
• Experience generating interactive dashboards with Claude is especially valuable; the team is a heavy adopter of AI tooling and the new hire is expected to be the same.
• Excellent communication skills, with the ability to work with cross-functional stakeholders and present complex analytical work to senior partners.
• Self-starter mindset: able to operate independently, demonstrate initiative, and drive work forward without hand-holding.
• Strong slide and presentation skills, with the ability to communicate clearly to broad and senior audiences.
• Prior experience at a tech, marketplace, or comparable company with mature metric pipeline infrastructure.
• Track record of metric definition, pipeline ownership, and stakeholder communication on internal-facing analytics work.
• Bachelor's degree in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research) is sufficient. Master's or PhD is a plus.

Tech Stack

• Python
• SQL