The Rundown AI, Inc.
About the role
As an early member of our Data Science and Analytics team focusing on our API, you will play a critical role in driving the growth and optimization of Anthropic's API products that power thousands of developers and enterprises building with AI. You'll work at the intersection of product strategy, customer insights, and revenue optimization to help scale our API platform from millions to billions of API calls while maintaining our commitment to safety and reliability. You will partner closely with product, engineering, and go-to-market teams to understand developer and enterprise customer behavior, identify growth opportunities, and drive data-informed decisions that shape our API roadmap. This role offers a unique opportunity to influence how AI is deployed at scale across industries while working with cutting-edge language models and developer tools. Responsibilities:
API Product Analytics : Deep dive into API usage patterns, developer adoption funnels, and enterprise customer behavior to provide actionable insights that drive product strategy and feature prioritization Revenue & Retention Analysis : Analyze customer lifecycle metrics, revenue retention patterns, and usage-based billing dynamics to identify opportunities for growth and reduce churn across our API customer base Developer Experience Optimization : Design and analyze experiments to improve API adoption, reduce time-to-value for developers, and enhance the overall developer experience across our platform ecosystem Customer Segmentation & Insights : Build sophisticated models to segment API customers by use case, company size, and behavioral patterns to inform targeted product development and go-to-market strategies Cross-Platform Analysis : Analyze customer behavior across Anthropic's ecosystem (1P API, Bedrock, Vertex AI) to understand platform preferences, switching patterns, and optimization opportunities Experimentation & A/B Testing : Design, execute, and analyze controlled experiments on API features, pricing strategies, and developer onboarding flows to drive measurable improvements in key metrics Predictive Modeling : Develop models to forecast API usage, predict customer growth potential, and identify early signals of expansion or churn risk Enterprise Customer Intelligence : Partner with sales and customer success teams to analyze enterprise customer usage patterns, measure feature adoption, and provide insights that inform account strategy You may be a good fit if you:
Have 6+ years of experience in data science or analytics roles, with significant experience in API products, developer tools, or B2B SaaS platforms Have 3+ years of experience working closely with Product or Engineering teams on API or developer-facing products, with demonstrated impact on product roadmap and strategy Possess deep expertise in Python, SQL, and statistical analysis, with experience analyzing usage-based billing models and API consumption patterns Have experience with enterprise customer analytics, including customer lifecycle modeling, retention analysis, and revenue optimization Understand developer ecosystems and have worked with API metrics such as adoption rates, integration patterns, rate limiting impacts, and developer onboarding funnels Have a track record of designing and analyzing A/B tests and controlled experiments in technical product environments Excel at translating complex API usage data into clear, actionable insights for both technical and business stakeholders Demonstrate a bias for action and ability to thrive in ambiguous, fast-moving environments where you must create clarity and drive forward progress Have experience working with high-volume, real-time data systems and understanding the technical constraints that inform product decisions Strong candidates may also have:
Experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem Background in analyzing multi-platform ecosystems (cloud providers, marketplaces, etc.) and understanding platform dynamics Experience with usage-based pricing models, API rate limiting strategies, and developer monetization Knowledge of enterprise sales cycles and experience supporting B2B sales teams with data insights Familiarity with cloud platforms (AWS Bedrock, Google Vertex AI) and their impact on customer behavior Experience building and maintaining data infrastructure for high-scale API products Background in customer research methodologies and survey design for developer communities
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As an early member of our Data Science and Analytics team focusing on our API, you will play a critical role in driving the growth and optimization of Anthropic's API products that power thousands of developers and enterprises building with AI. You'll work at the intersection of product strategy, customer insights, and revenue optimization to help scale our API platform from millions to billions of API calls while maintaining our commitment to safety and reliability. You will partner closely with product, engineering, and go-to-market teams to understand developer and enterprise customer behavior, identify growth opportunities, and drive data-informed decisions that shape our API roadmap. This role offers a unique opportunity to influence how AI is deployed at scale across industries while working with cutting-edge language models and developer tools. Responsibilities:
API Product Analytics : Deep dive into API usage patterns, developer adoption funnels, and enterprise customer behavior to provide actionable insights that drive product strategy and feature prioritization Revenue & Retention Analysis : Analyze customer lifecycle metrics, revenue retention patterns, and usage-based billing dynamics to identify opportunities for growth and reduce churn across our API customer base Developer Experience Optimization : Design and analyze experiments to improve API adoption, reduce time-to-value for developers, and enhance the overall developer experience across our platform ecosystem Customer Segmentation & Insights : Build sophisticated models to segment API customers by use case, company size, and behavioral patterns to inform targeted product development and go-to-market strategies Cross-Platform Analysis : Analyze customer behavior across Anthropic's ecosystem (1P API, Bedrock, Vertex AI) to understand platform preferences, switching patterns, and optimization opportunities Experimentation & A/B Testing : Design, execute, and analyze controlled experiments on API features, pricing strategies, and developer onboarding flows to drive measurable improvements in key metrics Predictive Modeling : Develop models to forecast API usage, predict customer growth potential, and identify early signals of expansion or churn risk Enterprise Customer Intelligence : Partner with sales and customer success teams to analyze enterprise customer usage patterns, measure feature adoption, and provide insights that inform account strategy You may be a good fit if you:
Have 6+ years of experience in data science or analytics roles, with significant experience in API products, developer tools, or B2B SaaS platforms Have 3+ years of experience working closely with Product or Engineering teams on API or developer-facing products, with demonstrated impact on product roadmap and strategy Possess deep expertise in Python, SQL, and statistical analysis, with experience analyzing usage-based billing models and API consumption patterns Have experience with enterprise customer analytics, including customer lifecycle modeling, retention analysis, and revenue optimization Understand developer ecosystems and have worked with API metrics such as adoption rates, integration patterns, rate limiting impacts, and developer onboarding funnels Have a track record of designing and analyzing A/B tests and controlled experiments in technical product environments Excel at translating complex API usage data into clear, actionable insights for both technical and business stakeholders Demonstrate a bias for action and ability to thrive in ambiguous, fast-moving environments where you must create clarity and drive forward progress Have experience working with high-volume, real-time data systems and understanding the technical constraints that inform product decisions Strong candidates may also have:
Experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem Background in analyzing multi-platform ecosystems (cloud providers, marketplaces, etc.) and understanding platform dynamics Experience with usage-based pricing models, API rate limiting strategies, and developer monetization Knowledge of enterprise sales cycles and experience supporting B2B sales teams with data insights Familiarity with cloud platforms (AWS Bedrock, Google Vertex AI) and their impact on customer behavior Experience building and maintaining data infrastructure for high-scale API products Background in customer research methodologies and survey design for developer communities
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