Intuit Inc.
Senior Technical Data Analyst
Intuit Inc., Mountain View, California, us, 94039
Intuit’s Global Business Solutions Group (GBSG) serves the needs of over 2 million small businesses and self-employed individuals. Our vision is to be the connected E2E platform that small and medium-sized businesses rely on every day to run and grow their businesses, delivering for our customers: double their revenue and double profitability.The Sales Capabilities Analytics team drives user and revenue growth using sales analytics, customer analytics, and sales channel optimization for the Small Business Group. We are an exciting, growing, and fun team that works with industry-leading analytics tools, techniques, and best practices.The Sales Capabilities Analytics group is looking to expand its capabilities in machine learning and data analytics to work closely with analysts, engineers, and sales leaders.Responsibilities
Solve for sales and finance leaders’ critical data needs in partnership with data engineering and sales tech.Apply data mining, LLM, and machine learning (both supervised and unsupervised) to build speech analytics and propensity models that can improve sales funnel and agent performance.Partner with cross-functional teams to design and build analytics and reporting tools that automate self-serve insights generation and improve experimentation/channel measurement frameworks.Excellent storytelling with data to educate and instill confidence, motivating stakeholders to act on recommendations.Proactively discover new data sources, improve existing data sources, and find areas of opportunity to optimize business performance. You need to be willing and able to do your own ETL and build data pipelines.Ability to work independently side-by-side with the sales team, data engineering, finance, sales operations, and sales tech on a regular basis.Minimum Requirements
Bachelor’s degree in Information Systems, Computer Science, Engineering, Applied Math, or equivalent work experience. Master’s preferred.Experience in data mining algorithms and statistical modeling techniques such as clustering, classification, regression, decision trees, neural nets, support vector machines, NLP text mining, and LLM.Experience in modern advanced analytical tools and programming languages such as R or Python with scikit-learn.Technical proficiency in SQL, Databrick, Tableau, and Qliksense.Solid communication skills: Demonstrated ability to explain complex technical issues to both technical and non-technical audiences.Can-do attitude, hands-on approach, and passion for data.
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Solve for sales and finance leaders’ critical data needs in partnership with data engineering and sales tech.Apply data mining, LLM, and machine learning (both supervised and unsupervised) to build speech analytics and propensity models that can improve sales funnel and agent performance.Partner with cross-functional teams to design and build analytics and reporting tools that automate self-serve insights generation and improve experimentation/channel measurement frameworks.Excellent storytelling with data to educate and instill confidence, motivating stakeholders to act on recommendations.Proactively discover new data sources, improve existing data sources, and find areas of opportunity to optimize business performance. You need to be willing and able to do your own ETL and build data pipelines.Ability to work independently side-by-side with the sales team, data engineering, finance, sales operations, and sales tech on a regular basis.Minimum Requirements
Bachelor’s degree in Information Systems, Computer Science, Engineering, Applied Math, or equivalent work experience. Master’s preferred.Experience in data mining algorithms and statistical modeling techniques such as clustering, classification, regression, decision trees, neural nets, support vector machines, NLP text mining, and LLM.Experience in modern advanced analytical tools and programming languages such as R or Python with scikit-learn.Technical proficiency in SQL, Databrick, Tableau, and Qliksense.Solid communication skills: Demonstrated ability to explain complex technical issues to both technical and non-technical audiences.Can-do attitude, hands-on approach, and passion for data.
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