Director, Data

Wunderman Thompson

Department: Data & Analytics

Expertise: Data

Location: Minneapolis, MN, United States

Who we are:

At Wunderman Thompson we exist to inspire growth for ambitious brands. Part creative agency, part consultancy and part technology company, our experts provide end-to-end capabilities at a global scale to deliver inspiration across the entire brand and customer experience.

We are 20,000 strong in 90 markets around the world; our people bring together creative storytelling, diverse perspectives, inclusive thinking, and highly specialized vertical capabilities to drive growth for our clients. We offer deep expertise across the entire customer journey, including communications, commerce, consultancy, CRM, CX, data, production, and technology.

Gain Theory (A Wunderman Thompson Company) is looking for a DCOE (Data Center of Excellence) Director to support the North America (NA) region. The director will have two primary responsibilities: the first is to drive and support global DCOE initiatives and projects, the second is to provide matrixed oversight data resources supporting NA clients. This individual will be an innovative, problem-solving networker who is motivated to drive data initiatives both globally and within NA.

Reporting to the Global DCOE lead, the director will need to collaborate with a diverse teams of client leads, data engineers, analysts, designers, solution owners, and various COEs in a global matrix structure. Our teams bring together cutting-edge data engineering, advanced analytics, unified measurement products and enterprise scalable engineering to build products that will shape the next decade of faster, smarter, data informed decision-making. We believe consumer privacy, client confidentiality, brand growth and user experience are essential to performance.

Key Responsibilities

DCOE Initiatives

  • Defining, scoping, supporting, and driving DCOE project (e.g. Common data sets, Data training, GTD1)
  • Defining, scoping, supporting, and driving custom client data projects as needed
  • Coordinating with other regional DCOE leads to ensure global consistency
  • Defining, documenting, and rolling out DCOE best practices
  • Actively participating and contributing to the Global Data Governance team
  • Coordinating with devops, product, and engineering to drive cross functional technology initiatives
  • Provide technical consultation to client leads for complex data requirements and needs North America Data Team
  • Coordinate with resourcing team to provide client leads with data scoping and resource estimates
  • Act as the data lead for assigned NA clients, being accountable for all data deliverables and timelines
  • Direct and lead data resources to support assigned NA clients on data techniques, best practices, and tools to enable them to better support their ongoing client data work
  • May include mentorship of other NA data resources including tasks such as informal check ins, connecting them to wider DCOE resources/training, allocating them to DCOE initiatives, etc.
  • Regularly meet with global data lead community for knowledge sharing

Qualifications

  • Bachelor’s Degree in business, Marketing, Statistics, Computer Science, Information Science, Engineering, or related quantitative field
  • In depth experience with all things data including ability to work with a variety of datasets from multiple sources, familiar with standard data processing tools/concepts (e.g. SQL, ETL), and experience driving robust QA processes
  • In depth experience of the advertising ecosystem (e.g. ad trafficking, Ad servers, DSPs, Media Strategy and Activation, etc.) and a working knowledge of appropriate metrics, measurement, and reporting
  • Can lead requirements gathering, project planning, and implementation for both cross functional internal data initiatives as well client-side data projects
  • Has project management skills including planning tasks and deliverables, managing timelines and risks, managing team resource allocation, and overseeing multiple simultaneous projects
  • Ability to manage and motivate Gain Theory team members
  • Organized, detail-oriented, QA-focused
  • Experience/familiarity with Multi-Touch Attributions solutions and/or Market Mix Modeling will be highly valued
  • Experience with key reporting solutions such as Tableau will be highly valued
  • Excellent written, verbal, and presentation skills

 

ABOUT GAIN THEORY:

Gain Theory is a global marketing effectiveness consultancy, empowering marketing and insight professionals to create agile, smarter, data-informed cultures using data, technology and advanced analytics.

As an independent practice within WPP, Gain Theory is trusted by clients around the world to enhance business performance in both the short and long-term by improving marketing effectiveness and efficiency, increasing baseline profits, growing market share and driving share price growth.

The global team consists of 200+ consultants, data scientists, mathematicians and marketing technology specialists who operate globally servicing 113 markets worldwide.

Gain Theory embraces and celebrates diversity, inclusivity, and equal opportunity. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. We are a worldwide agency network that represents global clients. The more inclusive we are, the better work we can create together.

At Wunderman Thompson, we are committed to actively building a diverse, equitable and inclusive workplace where everyone feels welcomed, valued and heard, and is treated with dignity and respect.  As leaders and creative partners across industries, it is our responsibility to cultivate an environment reflective of our greatest asset; our people. We believe that this commitment inspires growth and delivers equitable outcomes for everyone as well as the clients and communities we serve.

Wunderman Thompson is a WPP agency.  For more informationplease visit our website and follow Wunderman Thompson on our social channels via Twitter, Facebook, LinkedIn, and Instagram.  

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