Beaverton, Oregon, US
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Nike Direct Consumer Merchandising Analytics Manager

Country : USA USA

State : Oregon

County : Washington

Town : Beaverton

Category : Merchandising

Contract type : Permanent

Availability : Full time

Job description

We are hiring a Nike Direct Consumer Merchandising Analytics Manager for the Asia Pacific and Latin America geography
This person will be at the heart of the APLA Digital business and will inform and support partners to make decisions that will lead to the accomplishment of our goals. Focusing on managing Consumer (Members) lifecycle through merchandising analysis and marketplace insight delivery, it involves periodical reviews, supporting strategic projects and ad-hoc analysis. Collaboration with Consumer Construct, Merchandising, and Data Science Teams will be the key to your success to drive speed to market decisions. Projects will include assortment preparation support and impact of consumer segmentation initiatives.
This position requires a high-energy and self-motivated person with strong Retail Analytics background as well as Technical skills, all coupled with high detail-orientation and excellent written and verbal communication. The right individual will be on top of retail trends and understand the intricacies of consumer segmentation and lifecycle management. We are looking for someone who is passionate about working with numbers, who is highly technical but also has strong intuition for business.
- Bring a consumer view to measuring the efficiency and productivity of Nike Direct (retail) assortment
- Analyze product preferences and behavior of different consumer groups as well the impact different products have on Member segments
- Partner with Consumer Construct Leads to understand Member's behavior across Apps, product and retail platforms
- Collaborate with the APLA SNKRS leadership group to understand the performance and the opportunity of Nike's high heat business
- Understand the consumer engagement with our retail channels and how that leads to purchases
- Participate in Nike's long term product planning processes, bringing a consumer and segment perspective to the decision-making process
- Understand the interaction of Product Traffic, Conversion and inventory to drive in-season opportunities
- Drive the strategic development of this role, finding opportunities for new types of analysis and collaborating to build the capabilities to support it
- Handle the relationship, define the requirements, prioritization and roadmap for several data capabilities projects with Nike internal as well as external agencies partners
You will partner with the Analytics leads for Nike's Consumer Construct groups (Womens, Kids, Mens and Jordan) as well as support the geography team leading the High Heat business (SNKRS). You will work together with the Digital Commerce, Brick and Mortar and Member analytics teammates. In a broader sense, deliver analysis and insights to Merchandising and Retail teams and leaders. In summary, the person in this role will be a key contributor to the success of the business and the driver of data and insights informed decisions to our leaders across APLA.


- Bachelor's degree or higher in Business, Finance, Economics, Engineering, Statistics or similar fields, OR combination of relevant education, experience and training.
- Minimum 5 years of relevant professional experience in Digital Analytics, Retail Analytics, Customer Intelligence, Marketing Sciences or similar.
- Deep understanding of the potential and limitations of each area of analysis including Web analytics, Consumer Intelligence, Statistical analysis
- Clear knowledge of Retail Financials, Online Commerce and Retail KPIs and ROI, consumer analytics and omnichannel analytics
- Experience with different types of tools used in analytics including Visualization tools, Database clients (SQL), statistical tools, Python, Web analytics and clickstream, etc. Candidates without demonstrable SQL experience will not be considered.
- Strong communication skills both at a technical level as well as at a Financial/Business performance level. Demonstrable examples of using data to influence decision making required
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