Manager 2, Data Science

About the Role

Key Responsibilities

• Drive strategic thinking to optimize product and user experience efforts (inclusive of experimentation) for customer journeys, 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 grow product usage, 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.
• Promotes a scientific and engineering mindset to analytics. Uplevels team on analytics engineering practices, and teaches experimentation science and statistical modeling.
• 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 product 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.
• Establishes best practices including quality assurance, automation, code reviews, quality checks, and data alarms. Rolls up their sleeves when needed to write or review code, develop models, or create data visualizations for stakeholders.
• Fosters an environment for continued team exploration and learning.
• Leads inclusively, by fostering Intuit's values and cultivating an environment of diversity, inclusion and belonging. Actively supports DEI goals and leads by example.

Requirements

• 8+ years of experience working in web, product, marketing, or other related analytics fields. Ability to tell stories with data, educate effectively, and instill confidence, motivating stakeholders to act on recommendations.
• 3+ years working with customer data in product science, product analytics, customer analytics, customer insights, sales analytics, customer lifecycle marketing, or related field/function. Demonstrated ability to deeply analyze customer data to inform product, marketing and sales decisions.
• 3-5 years' experience managing data analysts, business intelligence engineers, data scientists or data engineers with a proven track record of building high-performing analytics and data science teams and developing successful analysts/data scientists.
• Strong product sense with a demonstrated ability to diagnose and solve real product problems.
• Solid modeling foundation is a plus, including hands-on expertise with data mining and statistical modeling techniques such as clustering, classification, regression, tree-based methods, neural nets, support vector machines, anomaly detection, and natural language processing.
• Experience with customer segmentation, data enrichment tools and technologies, and personalization at scale (preferably in a B2B context).
• Degree in engineering, computer science, information systems or equivalent experience required, Masters/MBA preferred.

Nice to Have

• Hands-on expertise with data mining and statistical modeling techniques such as clustering, classification, regression, tree-based methods, neural nets, support vector machines, anomaly detection, and natural language processing.
• Experience with customer segmentation, data enrichment tools and technologies, and personalization at scale (preferably in a B2B context).

Qualifications

• Degree in engineering, computer science, information systems or equivalent experience required, Masters/MBA preferred.