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Marketing Analytics Data Scientist
Lakeland, FL between Orlando and TampaPosted 1 weeks ago
onsite
Job Description
Publix is able to offer virtual/remote employment for this position in the following states: FL, GA, AL, TN, SC, NC, VA, KY
This role is responsible for developing and deploying advanced data science and machine learning solutions that drive business performance, enhance customer personalization, and optimize pricing, merchandising, and promotional strategies. The position leverages large-scale data analysis, predictive modeling, and AI-driven systems to generate insights, automate decision-making, and improve customer engagement across channels.
Additional responsibilities include:
This role is responsible for developing and deploying advanced data science and machine learning solutions that drive business performance, enhance customer personalization, and optimize pricing, merchandising, and promotional strategies. The position leverages large-scale data analysis, predictive modeling, and AI-driven systems to generate insights, automate decision-making, and improve customer engagement across channels.
Additional responsibilities include:
- developing and implementing scalable Data Science Analytical Solutions that rely on machine learning and artificial intelligence to automate and optimize key business processes and help improve efficiency and financial results
- providing research-based consultation and recommendations regarding the personalization of customer interfaces with Publix
- contributing to the design and measurement of customer personalization programs at the Marketing channel, omni-channel, product hierarchy, and store level
- analyzing customer, transaction, and campaign data to identify trends and patterns in marketing campaign performance and/or customer behavior
- building learning systems that monitor data flows and react to changes in customer preferences, network constraints, and business objectives
- manipulate large datasets to discover and extract meaningful business information using data mining, statistics, and machine learning techniques
- developing scalable, efficient processes for large scale data analyses, model development and model implementation
- analyzing and troubleshooting highly complex systems for accuracy, performance improvement and integration with changes to other enterprise systems