The Data Scientist works closely with Retail Technology, Media and Account Services teams to provide predictive modeling of Marketing, Direct & Digital Efforts. We are looking for a motivated Data Scientist and analytical thought leader. This is a rare opportunity to be part of a diverse and newly expanded analytics department and a great fit for a predictive modeler with a desire to impact business results.

Responsibilities

Apply specialized technical knowledge and expertise to perform reviews relating to the full life cycle of models, information technology applications, or risk management/analysis used across the company.
Collaborate and share knowledge with teams across the media organization, as appropriate. Build and maintain relationships with business partners at the manager and staff levels.
Use data analysis, mining, and migration techniques for enhanced targeting, audience segmentation, clustering, profiling, and regression analysis
Identify digital placement-level strengths and weaknesses across simultaneous campaigns and geographies
Develop and maintain internal automated reporting tools, documents, scoring systems, and dashboards for on-going and post-campaign reporting
Coordinate cross-functional reviews to discuss region- and campaign-specific findings and actionable recommendations for digital media campaigns built on various CPM, CPC, CPE, and CPA models
Identify and facilitate resolution of tagging issues in coordination with Traffic and Production teams focused on site-side tracking, reporting, and implementation
Provide client-facing/non-technical recommendations and insights, both in a written and verbal manner, that provide understandable and actionable optimizations.
Work with Media, Strategic Intelligence and Account Services teams to develop measurement plans to deliver on campaign and client objectives

Requirements

Bachelor’s degree in related field
Entry-Level and/or College Internship experience
Must demonstrate the ability to successfully develop and run analytics (scripts) using specialized tools and platforms, specifically, R, Python, SQL, and/or SAS.
Experience applying data synthesis, mining and regression techniques for enhanced targeting, audience segmentation, clustering, profiling, and insightful recommendations
Advanced knowledge of Microsoft Excel
General understanding of digital advertising, digital media strategy, ad placement type, placement-level insight, and standard media metrics is preferred
Experience with data orchestration tools such as Annalect Omni is preferred
Excellent verbal, written and interpersonal communication skills
Ability to work independently and as part of a team
Ability to manage multiple projects simultaneously while meeting deadlines
Regression modeling focusing on maximizing yield while measuring the diminishing returns of ad spend at scale for thousands of locations.
Data storytelling and presentation

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