Manager, Personalization Analytics

Responsibilities

• Use big data and advanced analytical techniques to optimize customer engagement and lifetime value.
• Utilize customer-level 1:1 analysis and modeling for targeting initiatives.
• Play a lead role in consolidating learnings toward personalization initiatives that help make data based targeting more potent over time.
• Oversee the activation of tests, ensuring essential model runs, segmentation, and timelines are provided to key stakeholders.
• Ensure relevant analytics assets and tests are documented, and insights are captured.
• Manage and influence direct reports, systems and projects to achieve unit goals per Kohl’s policies and practices.
• Provide leadership by exhibiting influence and expertise and driving results.
• Create and promote an effective work environment by developing a common vision, setting clear objectives, expecting teamwork, recognizing outstanding performance, and maintaining open communications.
• Develop staff through coaching, providing performance feedback, providing effective performance assessments and establishing performance and development plans.
• Influence, collaborate, and partner with teams and leaders across the organization.

Master’s degree in Statistics, Data Science, Business Analytics and Information Management, or related field of study and 2 years of experience in the job offered or any related occupation in which the required experience was gained. In lieu of a Master’s degree in Statistics, Data Science, Business Analytics and Information Management, or related field of study, the employer will also accept a Bachelor’s degree in Statistics, Data Science, Business Analytics and Information Management, or related field of study and 5 years of experience in the job offered or any related occupation in which the required experience was gained.

• Using Python, R, on cloud servers to explore business performance data to create insight. Methods can include clustering, market basket analysis, regression analysis, and descriptive analysis.
• Scaling predictive models and optimization algorithms for marketing use cases.
• Machine learning theory and techniques used for creating predictive models, including understanding of gradient boosting techniques and loss functions.
• Creating personalization models to improve targeting across channels.
• Developing and applying A/B testing frameworks to test model and marketing strategy effectiveness, proficient in a variety of bias correction methods and apply according to the specific situation.
• Creating reports about model/analysis results using data visualization with tools such as Google Slides/Worksheet, Tableau, Looker, Streamlit, or Power BI.
• Data ETL (extract, transform, load) with SQL or Google Big query, to pull and analyze large and complex datasets, proficient in advanced syntaxes.

To apply, email resume to , or submit a resume to , or submit a resume to  Must reference Job Title & Job Code: 000252.