eCommerce Analytics Manager
Exciting opportunity for an eCommerce Analytics Manager to join an fast-paced growing company in the Sandy Springs / Dunwoody area working with some of the largest brands in the country!
This is a brand new / greenfield role where you will set the tone for a new group within an excelling company that will facilitate the growth of some of the largest brands in the country. Each "brand" has their own tools and processes and as the eCommerce Analytics Manager, you will serve as an internal consultant responsible for developing/implementing and standardizing tools and processes across all brands to improve the use of online channels to boost market share and drive demand. The ideal candidate is an analytical thinker who thrives in a fast-paced team environment and can think at an enterprise level. This is not a heads-down role and you must be comfortable working with cross-functional teams such as brand marketing, business intelligence, data science, IT, design, and consumer product. This individual contributor role within shared services does offer growth opportunities to move into a leadership/management role if desired.
Enjoy this direct-hire position in the Sandy Springs that offers an excellent culture / environment, modern office space, fully stocked kitchen / break room with mini arcade feel, Summer and Winter Fridays where you can leave after 2:00pm (May - July and end of November - December) and flexible schedule!
- 5+ years eCommerce Analytics experience
- 5+ years of CRM execution tool experience (Salesforce, Unica, SAS, Marketo, etc)
- 3+ years of experience with CRM / database marketing and customer analytics (loyalty and retention)
- Excellent communication skills, high-energy, and consultative personality
- Shared Services
- Experience working on the Brand and Agency side
- Experience with omnichannel / target marketing
- Bachelor's Degree
Must be authorized to work in the U.S./Sponsorships are not available
Use Statistical Method
Analyze Performance Report
Make Strategic Recommendation
Analyze Statistical Data