Join our mission

Intuit is a global technology platform that helps consumers and small businesses overcome their most important financial challenges. Serving more than 100 million customers worldwide, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.

Overview

The Customer Success (CS) Data and Analytics team has an exciting opportunity to improve customer experiences using data. We are seeking an exceptional Sr. Technical Data Analyst to lead programs and enable world-class data and analytics capabilities to deliver better customer benefits and outcomes. This role will drive Customer Success data initiatives to enable the business to act quickly on data insights to inform better customer experiences and drive innovation.

You will draw upon solid analytical, critical thinking, and problem-solving skills to successfully drive analytical requirements with Data Engineering to deliver trusted and high quality data for analysts to leverage for critical insights. You have an ownership mindset with a strong willingness to take on new challenges with enthusiasm. You will quickly establish rapport, credibility, trust and respect throughout the organization at all levels, and be viewed as a team player. You will also partner closely with data engineering, product management, product development engineering, operations, and data analysts across Intuit.

This is an exciting time to join Customer Success at Intuit as we are building a service platform to help our customers beyond core product use. This is your opportunity to join this critical and transformational journey.

What you'll bring

• 5+ years of work experience involving quantitative data analysis
• Database experience with advanced SQL skills; experience researching and manipulating complex and large data sets; Hadoop experience a plus.
• Self-starter who seeks the problem with excellent problem-solving skills, creativity, and end-to-end quantitative and qualitative thinking
• Demonstrated ability to think end-to-end and experience working in a large matrixed organization, aligning cross functional stakeholders, negotiating trade-off discussions and prioritization, gathering business requirements, and delivering data solutions
• Excellent written and verbal communication skills with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders
• Ability to tell stories with data, be a champion for data across Intuit Customer Success, educates effectively, and instills confidence in recommendations, motivating others to act on them
• High level of professionalism, passion, strong organization, time management and task prioritization skills with attention to detail and bias to action
• Inquisitive, curious, and bias towards learning and continuous improvement
• Proficient in analytical and modelling tools, such as Python, R, or PyCharm
• Experience working with BI tools preferred such as Qlik, Tableau, PowerBI etc.
• Experience with instrumentation, clickstream data, data architecture, and complex business system interactions such as Salesforce, Amazon Connect, EWFM preferred
• Technical undergraduate degree (Engineering, Computer Science, Statistics, Analytics etc.) or equivalent experience

How you will lead

• Partner with product management/engineering, data engineering, and analytics teams to understand their project objectives and deliver standardized and consistent analytics data needed to drive AI-driven platforms
• Design and develop data preparation components and processes that extract and transform data across disparate database tables by creating aggregates tables for reporting and analytics, ensuring integrity of analysis data by developing the requirement specifications and assisting the development and testing of data tables
• Apply existing data mining techniques - descriptive and predictive modeling tools, and methodologies and/or design new data mining algorithms to drive solutions
• Collaborate with stakeholders and analysts to ensure data solutions are scalable, repeatable, effective, and meet expectations of various stakeholders
• Pursue data quality, troubleshoot data validation, and see issues to resolution
• Provide recommendations utilizing multiple types of data, business knowledge, and strategic assumptions when data does not exist
• Ensure data collection and processing is optimized to provide clear visibility into the impact and value of new initiatives and product releases
• Mitigate risk and solve problems through innovative ideas and solutions