Data Scientist

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
• Prior experience with data orchestration tools such as Annalect Omni
• 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