Senior Vice President Marketing Analytics

Newark, NJ Job ID: 10533 Job Category: Consumer Products

Job ID: EB-4632908467
Category: Analytics & Data Sciences
Location: Los Angeles, CA

Our client is hiring a Senior Vice President Marketing Analytics that oversees and coordinates data-driven insights, Technology and strategic thinking for a high-profile Marketing engagement.

You will lead efforts to better connect marketing data, engagement, and analytics for the client’s consumer marketing programs. You will work across multiple client teams and agencies to define and deliver on a Marketing Sciences vision, to holistically analyze marketing campaigns across channels and platforms and orchestrate and integrate insights in conjunction with client engagement, creative and strategy leads across the business.


• Identify, scope, propose, and direct the appropriate application of multi-agency marketing science and technology services.
• Design and recommend appropriate analytic methodologies, including but not limited to:

o Financial Modeling: Customer value, profitability, and lifetime value modeling.
o Descriptive Analytics: Heuristic segmentation at strategic and tactical levels.
o Predictive Analytics: Advanced statistical and econometric modeling techniques used to inform forecasting offer and sales effectiveness, promotional effectiveness, media optimization, pricing and churn elasticity, customer loyalty and satisfaction measures.
o Artificial Intelligence: Using supervised, semi-supervised, reinforcement learning, and unsupervised AI & ML methodologies
o Data-Driven Contact Strategy Development: Identifying and developing the optimal sequencing, frequency, offer and channel mix, achieved by leveraging multivariate testing methodologies, (e.g. fractional factorial design, Latin Square design), and decision rules.
o Digital Marketing Analytics: Analytics for digital marketing channels including tagging methodologies, viewability, touch attribution, funnel conversion analysis, etc. using tools like Google Analytics, Adobe Analytics, etc.
o Learning Agenda Development: Identification and management of KPIs aligned to strategic and tactical business objectives, insight generation and strategic recommendation.

• Author POVs and other IP covering recent trends and developments in marketing science and marketing technology, in particular as they apply in mobility and entertainment spaces.
• Codify best practices, package case studies, share methods and define new standards in collaboration with the global network team.
• Set and adjust priorities to reach goals across multiple projects and multiple Omnicom agencies.
• Create modeling datasets with vendor overlays, develop predictive models and place models in production for marketing efforts.
• Communicate all aspects of project: test design, findings and conclusions.
• Write and deliver final presentations to 100% completion.
• Handle most communication with clients and vendors and develop proposals for existing clients and new prospects.
• Provide management and direction on reporting, analytical, and modeling projects.


• 15+ Years of analytical experience, ideally marketing agency experience or management consulting practice.
• Strong knowledge of 1st, 2nd and 3rd party data.
• Extensive knowledge of direct marketing principles and best in class methodologies.
• Strong management skills and a proven track record of talent development.
• Advanced training and experience in statistical techniques such as: multivariate predictive modeling, multidimensional segmentation, factor analysis, lifetime value determinations, linear and logistic regression, CHAID analysis.
• Expertise in modern marketing customer data sources and services like CDP’s (Customer Data Platforms), DMP’s (Data Management Platforms), and ID Management, and how agencies can leverage client built, third party, and agency built data for improved marketing effectiveness.
• Expertise in digital marketing reporting, analytics, and attribution methodologies including multi-touch attribution, deterministic and probabilistic attribution, and tagging methodologies for improved attribution fidelity.
• Expertise in SAS, Python, R, Hadoop, SQL.
• Graduate Degree in a quantitative subject (Statistics, Mathematics, Operations Research, Economics) or Social Sciences, with heavy emphasis on quantitative methods (required).
• Advanced degree, (MSc / PhD) in a quantitative subject is preferred.
• Strong knowledge of experimental / multivariate test design techniques.