Head of Sales Analytics (Mailchimp)

Intuit Mailchimp is seeking an experienced analytics leader to lead & scale our sales analytics team. We have an exciting opportunity to evolve and accelerate the way we leverage behavioral and transactional data to drive revenue growth and improve customer retention.. This role will drive critical cross-functional strategies and will partner closely with sales, marketing, product management, data engineering, data analytics, data science and other cross functional partners. We're looking for someone who has a high bar for quality, intends to do the right thing and is driven by achieving and driving business outcomes.

Responsibilities

• Drive strategic thinking to optimize Sales Team efforts (inclusive of experimentation), based on customer segments, lifecycle stages, and other critical customer attributes.
• Represents analytics function on cross-functional leadership team and provides/inspires data-driven change around end-to-end customer experiences to improve retention and reduce churn.
• Develops and grows an exceptional team of data analysts and partners effectively with data engineers and data scientists; prioritizes the team's work to maximize effectiveness and impact both at the individual and team level.
• Partners with cross-functional stakeholders to better understand our users and create a single, accurate view of a customer across businesses to make decisions about how best to acquire/retain them, segment, identify high potential value, and proactively interact with them.
• Leads the full cycle of iterative big data exploration, including hypothesis formulation, algorithm development, data cleansing, testing, insight generation/visualization, and action planning.
• Collects, analyzes, and models available data to advance the customer/analytics space and build a broad understanding of the Mailchimp customers and relevant customer segments.
• Pursues data quality, troubleshoots data validation, and sees issues to resolution.
• Provides guidance and support to business leaders and stakeholders on how best to harness available data in support of critical business needs and goals.
• Establish best practices including quality assurance, automation, code reviews, quality checks, and data alarms. Roll up sleeves when needed to write or review code, or create data visualizations for our stakeholders.
• Foster an environment for continued team exploration and learning