What are the responsibilities and job description for the Digital Personalization Analytics Expert (Remote) position at KOHLS?
This position can be remote; however, if you reside near our offices in Menomonee Falls, WI, or New York City, NY, we request that you work onsite from Monday through Thursday, with the option to work remotely on Fridays.
About the Role
In this role you will ensure the creation of best-in-class digital experiences for Kohl’s customers using advanced analytics geared toward diagnostics, customer-level 1:1 modeling and in-market testing.
What You’ll Do
Leverage large-scale data and advanced analytics to optimize digital customer engagement and lifetime value
Lead end-to-end data science initiatives, from problem framing and exploratory analysis through model development, validation and production deployment
Drive consolidation of insights across digital initiatives to continuously enhance data-driven targeting and personalization strategies
Oversee test design and activation, ensuring model execution, audience segmentation and timelines are delivered effectively to stakeholders
Establish rigorous documentation standards for analytics assets, experiments and insights to enable knowledge sharing and scalability
Mentor junior data scientists, providing technical guidance and fostering a culture of continuous learning and excellence
Represent the Data Science team in cross-functional forums, independently communicating methodologies, results and strategic implications
Champion production-grade machine learning practices, promoting scalable code and robust deployment standards
Stay current on emerging data science methodologies and technologies, identifying and driving innovation opportunities that create business impact
Establish and maintain strong working relationships and achieve results by working collaboratively with others
Additional tasks may be assigned
What Skills You Have
Required
Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics or a related quantitative field
5 years (or 2 years with a Master’s degree) of progressively complex data science experience
Expertise in developing and deploying state-of-the-art algorithms using machine learning, statistical and optimization methods to power various aspects of highly complex business models and deliver value
Expert in using modern analytics tools, programming languages and cloud platforms (Python, R, Spark, SQL, GCP, etc.), as well as version control systems such as GitHub
Strong problem-solving skills with experience proposing rapid experiments to test the effectiveness of new strategies or initiatives and iterating quickly
Experience with data visualization technologies such as Streamlit, R Shiny, Looker, Qlik, Tableau, etc.
Preferred
Master's degree and/or Ph.D.
Digital / Ecommerce data science experience
Retail and Marketing experience