Senior Revenue Analytics Analyst

You will translate pre-sales, consumption, pipeline, and sales-efficiency questions into analytical requirements. You will build maintainable business intelligence and AI solutions for trial management, adoption, conversion, win rates, and sales metrics. You will define stakeholder and engagement data models, apply segmentation, cohort analysis, and A/B testing, and document data logic and methodologies. You will also improve data quality, consistency, and performance while communicating insights and recommendations to technical and non-technical stakeholders.

Responsibilities

• Translate pre-sales engagement, consumption, pipeline, and sales-efficiency questions into analytical requirements
• Design and build AI and analytics solutions for trial management, win rates, adoption, conversion, and sales metrics
• Create maintainable business intelligence and AI solutions that enable customer-facing teams to monitor performance and act
• Define requirements for stakeholder and engagement data models
• Apply segmentation, cohort analysis, and A/B testing to inform scaled engagement strategies and forecast digital-program impact
• Share sales analytics best practices, document logic and methodologies, and guide partners and analysts in using data

Requirements

• Experience in analytics roles focused on pre-sales motions and SaaS
• Experience analyzing customer engagement, adoption, and health across the customer lifecycle
• Experience combining data from multiple customer and go-to-market systems
• Proficiency writing complex SQL queries with joins, aggregations, common table expressions, and conditional logic
• Ability to analyze pipeline, pre-sales engagements, trial success rates, and sales metrics using SQL and Python
• Experience collaborating with Sales, Field Operations or RevOps, Finance, and Customer Success partners
• Experience working with Snowflake, dbt models, and other data sources
• Ability to communicate analytical findings and recommendations to technical and non-technical audiences
• Experience collaborating with cross-functional partners in a remote, distributed environment
• Attention to data quality, consistency, performance, assumptions, logic, and edge cases
• Openness to generative AI and experimentation techniques

Benefits

• Health, financial, and well-being benefits
• Flexible Paid Time Off
• Team Member Resource Groups
• Equity compensation
• Employee Stock Purchase Plan
• Growth and Development Fund
• Parental Leave