Data Scientist - Marketing Analytics Team; Hybrid - Seattle

We are looking for a creative, curious, and passionate Data Scientist to join our Marketing Analytics team as a Data Scientist II. In this hands-on role, you will build end-to-end data products and machine learning models that transform marketing data into actionable insights and directly inform marketing strategy and investments. The Data Scientist role on the Marketing Optimization Analytics team is responsible for building end-to-end Machine Learning based Analytic Data Products that will directly impact short-term and long-term marketing strategy.

This person should utilize proper Data Science techniques and have experience across the full-stack. The role has an opportunity to tackle challenges from ideation to insights delivery, with visibility across the leadership organization.

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. We welcome your curiosity about the business, your passion to unlock rich, nuanced insights from complicated data and the desire to communicate those insights in a way that builds confidence and drives positive business outcomes.

We are committed to building teams that reflect the diversity of our customers and active inclusion is core to how Nordstrom wins. We’re an equal opportunity employer and encourage individuals from all backgrounds to apply. If the idea of making a difference in this vibrant intersection of fashion, data science, and technology excites you, join our world-class data science team!

A day in the life...

• Develop and implement analytics applications to extract meaningful insights from large, disparate data sources using Python, R, SQL, and data visualization tools.
• Build and enhance customized marketing mix models to connect marketing activities to short-term and long-term business outcomes.
• Optimize marketing investments by leveraging data-driven insights from modeling, forecasting, simulations, and testing.
• Design and analyze controlled experiments and A/B tests to validate model performance.
• Liaise with our external measurement vendors (MMM, testing, tracking, etc. ) to ensure robustness of their models and our internal models.
• Build and deploy robust data models that facilitate scalable statistical modeling and deep dive analyses for marketing use cases.
• Collaborate with our partner teams to create data science products and solutions for stakeholders, translating questions to robust answers efficiently.
• Perform large-scale statistical analysis and develop and apply segmentation, predictive models, and forecasting models to key business problems.
• Work within and across teams to develop and deploy data products and data-driven software, to provide analytical insights.
• Collaborate with and support consulting analytics teams on needs for ad-hoc analyses.
• Lead code and documentation reviews, educating the adoption of Data Science/Machine Learning best practices within the center of excellence.

Minimum qualifications include…

• 5+ years hands-on professional experience in Data Science and Analytics.
• 3-5+ years of strong coding skills in at least one statistical or programming language (e.g. R, Python) to import, process, summarize, and analyze data.
• Experience with utilizing data visualization tools to tell compelling data stories (e.g. Tableau, Shiny, Streamlit)
• Bachelor’s degree in mathematics, statistics, computer science, economics, operations research or in a quantitative field (or equivalent experience).
• Expertise in statistical modeling, experimental design, inferential statistics, and machine learning (with particular emphasis in causal measurement, marketing mix models, attribution models, and digital marketing analytics).
• Familiarity with marketing modeling techniques such as ad stock and carryover effects, the different types of transformations to capture diminishing returns effects in linear models, modeling approaches for capturing synergistic effects of media investments, creative decay/wear-in/wear-out, full funnel measurement.
• Experience in bridging bottoms-up marketing measurement (like MTA) with top-down approaches (like…