Supervisor, Marketing Science

As a Supervisor on the Marketing Science team, you will develop actionable insights through quantitative analysis, innovative thinking, and your industry knowledge to be a key contributor towards tactical and strategic efforts. You will use your strong analytic and technical knowledge to evolve campaign and strategic deliverables that meet our client’s business needs. You will be expected to be able to manage both people and process across multiple Marketing Science functions.

• Client Relationship Management, Growth & Retention Client Presentation:
  Present findings/insights as well as methodology/data approaches reliably to clients through a variety of different presentation opportunities
• Team Operations Collaboration:
  Connect across planning, investment, and technology teams to ensure holistic understanding of data
• Management:
  Start your management career by having Associate, Sr. Associate and Associate Managers reporting into you and managing their workload and career development
• Audience Discovery & Strategy Data Analysis:
  Become more seasoned in audience definition, creation and strategy using multiple data sources
• Data Analysis Management:
  Manage your team to organize and analyze data and facilitate insight generation for which you will be responsible
• Data Sources:
  Employ solid understanding of Audience data sources and how to best leverage them for each type of analysis
• Measurement & Reporting Measurement:
  Develop breadth of knowledge measurement strategy, frameworks and technology
• Benchmarks & Goals:
  Set benchmarks and targets based on historical campaign data
• Reporting & Optimization:
  Oversee and QA the development of reports and directing optimization initiatives
• Insights:
  Hone the ability to know what an insight is, and developing them for the campaigns
• Data Strategy & Technology Data Technology Utilization:
  Manage your team to oversee automation and improve processes for efficiencies
• Data Management:
  Be accountable for the maintenance and QA of data systems and processes used for reporting and on-Going data analysis
• Data Visualization:
  Develop advanced Dashboards in visualization tools such as Tableau/Qlik View/Looker
• Ad Operations:
  Apply advanced understanding of Ad Operations and QA procedures
• AdTech/Mar Tech:
  Evaluate and compare data, ad and Mar Tech vendors

• Client:
  Experience partnering with mid-level and junior clients on key deliverables
• Management:
  Prior management of teams of 1+ Marketing Science staff including Assoc. Manager/Sr. Analyst and below
• Data Knowledge:
  Broad experience using different types of behavioral data and/or syndicated research data sources
• Analytic Mindset and Creativity:
  Ability to creative problem solve
• Cross-Channel Analytics:
  Solid understanding of offline and online channel KPIs
• Structured analysis/statistical understanding:
  Application of basic statistical methods to data analysis
• Media Foundations:
  Solid foundation of understanding media strategy, budget setting and channel selection
• Data Science:
  Experience managing or applying more sophisticated advanced analytics/statistics using code
• Process Management:
  Basic experience creating documentation and development of repeatable, scalable processes

• Strong proficiency with MS Excel, PowerPoint are a must
• Breadth of experience using
• Ad-serving and web analytics tools (DCM, DV360, IAS/Moat, Facebook Advanced Analytics, Google ADH, Google Analytics, Adobe, etc.)
• Syndicated research sources/tools (Gfk, MRI, Simmons, Scarborough, IMS, Nielsen, com Score)
• Cross-media brand lift research (Kantar, Lucid, etc.)
• Applications of at least two of the following
• Data visualization” tools such as Tableau, Datorama, Alteryx
• Advanced analytics software package: SQL, R, Python or other
• Concepts of database design and SQL

• Experience:
  
  3-5 years of experience, preferably in marketing analytics
• Analytic Capabilities:
  Ability to think logically and use quantitative techniques to solve problems such as campaign analysis, optimization, data management, data operations and/or predictive modeling
• Education:
  
  Bachelor’s degree in math, economics, engineering, social sciences, finance,…