Manager Customer Lifecycle Analytics (Hybrid - Seattle)

$105,000 - $199,000/Yr

Nordstrom - Seattle, WA

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