Manager - Decision Support (Loyalty & Payments)
San Francisco, CA

Job Description

Data and Analytics organization is chartered with unlocking the power of data and analytics to enable better decision making consistently and confidently across Gap Inc. This organization is also responsible for building the Data and Analytics Platform on behalf of the entire organization in partnership with GapTech (IT team) and scale our capabilities across the enterprise. Decision Support team within Data and Analytics organization partners with brands and functions to drive business outcomes through adoption of analytics.

Reporting to the Sr. Director of Decision Support, the Manager, Decision Support is focused on partnering with Gap Inc Loyalty and Payments team to drive success of Loyalty and Credit Card programs.

* Perform analysis on customer and transaction data to support strategic initiatives and clearly communicate and present insights to customer and loyalty teams and leadership.
* Continually evolve and improve our marketing analytics capabilities and tools, including reporting capabilities and dashboards to provide insight into performance and customer trends.
* Partner with loyalty and payments, data science and testing teams to design, execute and analyze tests for performance and loyalty programs
* Express the voice of the customer during internal decision- making processes by using data storytelling as a method to communicate, and data and analysis to discover and unlock hidden insights
* 5 years of experience in customer or marketing analytics preferably in a multi-channel retail environment
* Analytical experience including regression modeling (Linear, Logistic) and strong foundational statistical knowledge.
* Experience manipulating large scale datasets using SQL
* Experience with R, Python, and SAS for data manipulation, modeling, and summarization
* Advanced Excel and PowerPoint.
* Experience with visualization tools such as Tableau, Power BI
* Strong business acumen and presentation skills
* Bachelor's degree in Statistics, Economics, Analytics, Data Science or other quantitative, technical, or social science field required. MS Degree preferred.