Manager, Marketing Channel Analytics (Hybrid, Seattle)

Nordstrom’scentralized Customer Analytics team focuses on supporting executive management with robust decisionsupportdata science. We build data science products and provide analytics consulting in support of strategic business decisions, including customer segmentation, marketing, company strategy, and digital experience. We work as the quantitative right-hand for the executive team with a passion for supporting data-driven decision making, a devotion to advanced techniques, along with a creative team spirit!

We are looking for aManagerMarketing Mix Modeling.This role sits at the center of a modern measurement stacksupportingMarketing Mix Modeling (MMM)and macro-level regression/econometricanalysis,andserves as the analytical backbone for marketing investment decisions across the enterprise.The ideal candidate is a creative self-starter and strong technical contributor who is always looking for new opportunities to solve business problems with data-driven tools, with a particular focus onoptimizingmarketing investment through a variety ofstatisticalmodels. The role has an opportunity to tackle challenges from ideation toinsightsdelivery, with visibility across the leadership organization. This individual should have a high degree of curiosity about the business and the skills to discover impactful insights from data and communicate those insights in a way that builds confidence and enables decisions that drive business value. 

Essential Functions and Work Duties

• Lead a team of up to four analystsand data scientists within the Nordstrom MarketingAnalytics teamsupporting foundational marketing measurement tools, frameworks, models, & attribution.

• Analytical owner of Nordstrom’s MMMincludingexisting modelrefits,modelvalidations,&incorporating incrementality tests, geo-experiments, and attribution data toenhance & improve model performance.

• Diagnose and resolve modeling challenges such asadstockdecay, multicollinearity, and channel saturation curves 

• Optimizemarketinginvestmenttoward ROAS,LTV:CAC, & customer targets.

• Bring data to life through storytelling in a clear and meaningful way to audiences with mixed levels of technicalexpertise.

• 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.

• Conduct scenario and sensitivity analysis to stress-test marketing plans against varying economic conditions, resulting in budget optimization recommendations

• Present the results to the stakeholders and guide them to make the best use of the insights for their purposes anduse-cases.

• Compile, cleanse, & analyze data to drive actionable outcomes in support of businessobjectives.

• Use advanced analytical and statistical practices to create thorough and actionable insights.

• Deliverhigh qualitysolutions and recommendations to a variety of problems both independently and through the collaboration with team members and business partners to drive outcomes.

• Proven leadership and management skills withdemonstratedskills in setting organizational vision and supporting strategies, building strong, effective, and self-directed teams.

Minimum qualifications include…

• Bachelor’s degree in mathematics, statistics, computer science, economics, operations research or in a quantitative field (or equivalent experience).

• 4+ years hands-on professional experience in Data Science and Analytics, with a focus on Marketing & Media Channel analytics roles. 

• 3-5 years of strong coding skills in at least one statistical or programming language (e.g.SQL,R, Python) to import, process, summarize, and analyze data,while drawing conclusions and making recommendations.

• 3+ years of experience with advanced BI visualization (Tableau or Looker preferred).

• Fluency with descriptive and inferential statistical techniques, including experimental design (DOE) concepts and their application.

• Proficiencywith 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. 

• Background in retail, e-commerce, or omnichannel business models