Manager 2, Data & Analytics (GBSG)

Job Overview

The Data Analytics team is searching for a talented Manager 2, Data and Analytics to

lead a team of Product Analysts supporting the Canadian Business. We are an exciting, fast

paced, and innovative team, leveraging industry-leading tools and best practices.

As a Manager 2, Data and Analytics, you will shape the vision and strategy of Product

Analytics for Quickbooks Canada as well as our ecosystem of products with the Global Business Solutions Group (GBSG). Working closely with our Product Team, you will lead and mentor a group of analysts to develop insights, lead experimentation, and drive key business results.

You are a tech forward leader who effectively communicates with both technical and

non-technical teams, in order to effect change for our customers.

You will take complex concepts and communicate them to both technical and non-technical leaders in order to effect change for our customers. You will be an instrumental leader in shaping the strategy and future of the Quickbooks Product. Working across Intuit AI, Data Engineering, and Product you will drive an integrated plan to grow and scale the Canadian Product Roadmap.

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.
• Establish 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 our stakeholders.
• Foster an environment for continued team exploration and learning
• Lead experimental designs and measurement plans

Qualifications

• 3-5 years of leading an analytics or data science team
• 5-8+ years of experience working in product, marketing, web, or other related analytics/data science fields
• Highly proficient in SQL, Tableau, and Excel
• Experience with programming languages including R or Python
• Excellent problem-solving skills and end to end quantitative thinking
• 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.
• Great communication skills: Demonstrated ability to explain complex technical issues to both technical and non-technical audiences
• Bachelor's degree in Computer Science, Statistics, Economics, Mathematics, Data Analytics, Finance, Advanced Analytics preferred or equivalent work experience