Senior Staff Data Scientist at Intuit
Mountain View, CA 94043, USA -
Full Time


Start Date

Immediate

Expiry Date

09 Oct, 25

Salary

0.0

Posted On

10 Jul, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Statistics, Analytics, Duplication, Fintech, Mathematics, Teams, Product Strategy, Computer Science, Strategic Insights, Key Metrics, Predictive Modeling, Econometrics, Risk, Data Science, A/B Testing, Data Driven Decision Making, Machine Learning, Communication Skills

Industry

Marketing/Advertising/Sales

Description

OVERVIEW

Intuit’s Global Business Solutions Group (GBSG) is dedicated to creating tools and services that dramatically increases the ability of small-medium businesses (SMBs) to manage cash flow. At the center of this mission, the QuickBooks Money team is developing innovative tools to help customers get paid faster and with confidence. Our expanding suite of offerings and new go-to-market strategies aim to further enhance SMBs’ ability to accept payments seamlessly. The Sales Data Science team on the GBSG Data & Analytics organization’s mission is to deliver and drive business impact by developing insights, models, and strategic thought partnership that helps accelerate GBSG’s growth. We partner with Sales, Product, Finance, Business Operations, Design and Engineering teams to foster data-driven decisions through strategic thinking, data analysis, experimentation, and predictive analytics. As a Senior Staff Data Scientist on the Sales Data Science team partnering with our Money Growth Mission Team, you will dive deep into our data to uncover actionable insights and make recommendations that will influence the company’s strategic decisions, especially with improving Sales efforts. The ideal candidate will have a strong background in quantitative analysis using large data sets, demonstrated growth hacking experience, and in data-driven decision making.

Responsibilities
  • Conceptualize business problems or opportunities, formulate hypotheses and goals, key metrics and make actionable recommendations
  • Drive strategic insights through effective storytelling with data, to educate and instill confidence, motivating stakeholders to act on recommendations.
  • Develop predictive models, conduct experimentation beyond A/B testing, and generate actionable customer insights that inform Sales innovation
  • Build and apply durable customer segmentation patterns to renew targeting, positioning, and customer experience
  • Partner closely with Sales, Product, Marketing, Engineering, Design, and Analytics leaders to deliver insights that drive product strategy and growth
  • Translate complex data insights into actionable recommendations for technical and non-technical stakeholders, and business leader
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