Director, Analytics
PHD UK - New York, New York, us, 10261
Work at PHD UK
Overview
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Overview
In order to make an application, simply read through the following job description and make sure to attach relevant documents.
Summary Of Role
As a Director on the Marketing Science team, you will lead the direction of an analytics program, manage a team, and deploy both strategic and campaign work. You will be provided opportunity to and expected to own key client program manager relationships. You use your strong analytic and technical knowledge to assume accountability our client’s business performance that result in award winning, case study work, while also advancing your career. Areas of Responsibility:
Client Relationship Management, Growth & Retention
Client Trust: Lead and own key client relationships, building trust through those relationships and positively driving the client’s business. Client Presentation: Build your confidence further with presentation skills and being quick on your feet when asked tough client questions. Collaboration: Partner with client leadership teams and planning to ensure client satisfaction Thought Leadership: Contribute to insights and thought leadership around business and media strategy for client facing deliverables. Communication: Become stronger at explaining complex concepts in a simple manner, bring experience-based opinions with confidence, distill evidence-based results into bullets. Business: Be responsible for the retention of Marketing Science scope, and positive client satisfaction scores.
Team Operations
Team Leadership: Be responsible for bringing leadership to the account and the broader Marketing Science team. Team Management: Grow your management career by having Associate, Sr. Associate, Associate Managers, Managers or Associate Directors reporting into you and managing their workload and career development. Hiring: Lead/Participate in the hiring process for the rest of the Marketing Science team. Estimates: Help to estimate time to create deliverables and support the Marketing Science lead in scope development and management.
Audience Discovery & Strategy
Audience Strategy: Collaborate with Planning to create the macro audience strategy for the account overall and at the campaign level when needed. Data Strategy: Oversee and direct the Data Science team on advanced audience query definition and development. Data Analysis: Lead advanced analysis of Audience data using multiple data sources to help direct overarching audience strategy. Data Analysis Management: Manage your team in organizing and analyzing data to facilitate insight generation for which you will be responsible. Data Sources: Use advanced understanding of Audience data sources to best leverage them for each type of analysis.
Measurement & Reporting
Measurement: Guide team in advanced measurement strategy, frameworks and technology. Benchmarks & Goals: Oversee the creation of benchmarks and targets based on historical campaign data. Reporting & Optimization: Be accountable for the quality of reports and the insights generated. Test Design: Create the design and lead development of learning agendas and test plans. Attribution: Direct and collaborate with Data Science on attribution design and analysis. Insights: Ensure macro insight development for campaign performance and optimization that ladder up to the overall strategic objectives of the account.
Data Strategy & Technology
Data Technology Utilization: Coordinate and oversee the Data Operations team for automation and improved processes for efficiencies. Data Management: Be accountable for the overall health of the data on the account, and management of the staff who are responsible for it. Data Visualization: Provide design direction and requirements gathering support for any data visualization. Test Deployment: Be accountable for ensuring quality of test deployment working with your team. Attribution Deployment: Coordinate with Data Science on attribution deployment and data collection. Ad Operations: Apply advanced understanding of Ad Operations and QA procedures. AdTech/MarTech: Evaluate and compare data, ad and MarTech vendors. Data Acquisition: Identify and evaluate of new data sources and the purchase of those data sources if necessary, for the account.
Desired Experience
Client Relationships: Experience leading and partnering with key decision-making clients. Management: Prior management of teams of 3+ Marketing Science staff including Associate Director and below. Business: Contributor toward growth and revenue goals through retention of clients. Data Knowledge: Broad experience using different types of behavioral data and/or syndicated research data sources. Data Strategy: Experience developing or contributing to Data Strategy and knowledge of 2nd and transparent 3rd party (non-DMP) data sources for the purposes of data partnerships and audience building. Strategic Mindset and Creativity: Proven ability to deeply understand the client’s business and bring strategic business thinking to drive the most effective media, audience and data strategy in partnership with planning. Cross-Channel Analytics: Experience with marketing mix modeling/econometric analysis and Multi-touch attribution for offline and online channels. Working understanding of offline and online channel KPIs. Media Foundations: Advanced understanding across client verticals of media strategy, budget setting and channel selection. Survey Design: Solid understanding of quantitative and qualitative survey design and analysis experience o Data Science: Ability to manage and direct Data Science staff and understand their work at a detailed enough level to ensure methodology and accuracy. Structured analysis/statistical understanding: Experience structuring analyses to get the most accurate read. Knowledge of statistical significance and ability to ensure and communicate relative confidence and risk levels.
Desired Technical Skills
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.) Behavioral data sources (Acxiom, Experian, Clickstream, Location, IRi, Liveramp) Syndicated research sources/tools (Gfk, MRI, Simmons, Scarborough, IMS, Nielsen, comScore) Cross-media brand lift research (Kantar, Lucid, etc.)
Experience with two or more
Data visualization tools such as Tableau, Datorama, Alteryx SQL, R, Python or other advanced analytics software packages Concepts of database design and SQL
Requirements
Experience: 8-10 years of experience, preferably in marketing for at least 5-7 years 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, analytical fine arts, or business/marketing fields, masters or work equivalent experience a plus
This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on relevant experience, other job-related qualifications/skills, and geographic location (to account for comparative cost of living). The Company reserves the right to modify this pay range at any time. For this role, benefits include: health insurance, vision insurance, dental insurance, 401(k), Healthcare Flexible Spending Account, Dependent Care Flexible Spending Account, vacation days, sick days, personal days, paid parental leave, paid medical leave, and STD/LTD insurance benefits.
Compensation Range
$150,000—$170,000 USD
This role is hybrid, requiring three (3) days per week in the office. The remaining two (2) days may be worked remotely. Specific in-office days will be discussed during the interview process, with flexibility to align with team needs. Please note that the number or required in-office days may be adjusted over time, potentially increasing the number of required in-office days based on business needs.
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Seniority level
Seniority levelNot Applicable Employment type
Employment typeFull-time Job function
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