Nordstrom - Seattle, WA

posted 27 days ago

Full-time - Manager
Hybrid - Seattle, WA
10,001+ employees
Clothing, Clothing Accessories, Shoe, and Jewelry Retailers

About the position

The Manager of Customer Lifecycle Analytics at Nordstrom is responsible for leading a team that focuses on optimizing lifecycle marketing strategies through data-driven insights. This role involves collaborating with various stakeholders to support customer acquisition, retention, and reactivation efforts, while utilizing advanced analytical techniques to drive business value. The position requires a blend of technical expertise and creative problem-solving to effectively communicate insights and influence strategic decisions within the organization.

Responsibilities

  • Lead a team of up to four analysts and data scientists within the Nordstrom Marketing Analytics team.
  • Partner with Lifecycle Marketing to ideate, define, test, and scale initiatives focused on growing active customers.
  • Bring data to life through storytelling in a clear and meaningful way to audiences with mixed levels of technical expertise.
  • Support various insights, testing, reporting, and optimization across the customer lifecycle (acquisition, activation, retention, and reactivation).
  • Manage and balance projects across competing priorities to focus on the most impactful work to maximize the value of your work to the business.
  • Partner with key stakeholders to define success and develop measurement frameworks.
  • Contribute & implement experimental design & test/learn frameworks across audiences, leveraging a full suite of marketing channels (email, direct mail, social media, TV, etc.).
  • Present the results to the stakeholders and guide them to make the best use of the insights for their purposes and use-cases.
  • Compile, cleanse, & analyze data to drive actionable outcomes in support of business objectives.
  • Use advanced analytical and statistical practices to create thorough and actionable insights.
  • Deliver high quality solutions and recommendations to a variety of problems both independently and through collaboration with team members and business partners.

Requirements

  • 5+ years hands-on professional experience in Data Science and Analytics, with a focus on Marketing & Customer analytics roles.
  • 3-5 years of strong coding skills in at least one statistical or programming language (e.g. R, Python).
  • Experience with utilizing data visualization tools to tell compelling data stories (e.g. PowerBI, Tableau, Looker).
  • Bachelor's degree in mathematics, statistics, computer science, economics, operations research or in a quantitative field (or equivalent experience).
  • Fluency with descriptive and inferential statistical techniques, including experimental design (DOE) concepts and their application.
  • Proficiency with statistical techniques and when best to apply given current situation.
  • Proficient in extracting large data sets from various relational databases using SQL (Big Query, Amazon Redshift, Oracle, Teradata preferred).
  • Prior experience supporting teams of data analysts and/or data scientists.

Nice-to-haves

  • Strong critical thinking and storytelling skills.
  • 5-8 years of experience analyzing complex data, drawing conclusions, and making recommendations.
  • 5+ years of experience developing and deploying production-level SQL queries.
  • 5+ years of experience with advanced BI visualization (Tableau or Looker preferred).
  • Professional experience using R or Python in analytics capacity.
  • Direct experience working with marketing channel optimization, customer lifecycle marketing, or customer loyalty programs is strongly preferred!
  • Experience working with Customer Data Platforms (Treasure Data, Blueshift, Adobe Experience Platform).
  • MS or PhD in mathematics, statistics, computer science, economics, operations research or in a quantitative field (or equivalent experience).
  • Familiarity with digital tactics, targeting and customer segmentation, lifetime value forecasting, and incremental response modeling.

Benefits

  • 401(k)
  • Dental insurance
  • Disability insurance
  • Employee assistance program
  • Health insurance
  • Life insurance
  • Paid time off
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