Nordstrom’s centralized Customer Analytics team focuses on supporting executive management with robust decision support data 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 a Manager Marketing Mix Modeling. This role sits at the center of a modern measurement stack supporting Marketing Mix Modeling (MMM) and macro-level regression/econometric analysis, and serves 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 on optimizing marketing investment through a variety of statistical models. The role has an opportunity to tackle challenges from ideation to insights delivery, 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 analysts and data scientists within the Nordstrom Marketing Analytics team supporting foundational marketing measurement tools, frameworks, models, & attribution. 

• Analytical owner of Nordstrom’s MMM including existing model refits, model validations, & incorporating incrementality tests, geo-experiments, and attribution data to enhance & improve model performance.  

• Diagnose and resolve modeling challenges such as adstock decay, multicollinearity, and channel saturation curves  

• Optimize marketing investment toward ROAS, LTV:CAC, & customer targets. 

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

• 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 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 the collaboration with team members and business partners to drive outcomes. 

• Proven leadership and management skills with demonstrated skills 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. 

• 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.  

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