Senior Associate, Business Analytics

PHD is a global communications planning and media buying agency network delivering smart strategic thinking and creative innovation for the world’s leading brands. Brilliant media thinking is in our DNA. A culture of thought-leadership, creativity and innovation has seen us grow from a challenger agency in the UK, to a global leader with over 6,000 employees in over 100 offices worldwide. We combine the latest industry insight with the best creative minds to produce planning innovation and create award-winning work for some of the world’s largest advertisers. Finding a better way is our ethos and sums up how we approach everything – from a new client brief to the way we work.

As a Senior Associate on the Marketing Science team, you will develop actionable insights through quantitative analysis, innovative thinking, and your growing industry knowledge. You will use your strong analytic and technical knowledge to design, produce, automate and evolve reports. You will be a proactive collaborator in insight generation and evolution of advertising programs that are proven to drive business results.

Areas Of Responsibility

• Team Operations
• Collaboration: Connect across planning, investment, and technology teams to ensure holistic understanding of data
• Self-Management: Manage day-to-day tasks, ensuring understanding of proper priorities

• Audience Discovery & Strategy
• Data Analysis: Implement analysis plans and support audience insight analysis across multiple data sources
• Data Analysis Management: Structure data in efficient manners for performing analysis

• Measurement & Reporting
• Measurement: Apply advancing foundational knowledge of measurement strategy, frameworks and technology
• Benchmarks & Goals: Learn how and assist in setting benchmarks and targets based on historical campaign data
• Reporting & Optimization: Produce of campaign reports and analyses according to measurement plans
• Insights: Learn the basics of how to develop an insight and apply knowledge to clearly create key takeaways from analyses

• Data Strategy & Technology
• Data Technology Utilization: Identify opportunities to automate analyses and identify more efficient processes
• Data Management: Maintain and QA data systems and processes used for reporting and on-going data analysis
• Data Visualization: Develop Dashboards in visualization tools such as Tableau/QlikView/Looker
• Ad Operations: Learn and apply advanced understanding of Ad Operations
  

Desired Experience

• Data Knowledge: Experience with different types of behavioral data and/or syndicated research data sources
• Analytic Mindset and Creativity: Ability to creatively problem solve
• Cross-Channel Analytics: Working understanding of offline and online channel KPIs
• Structured analysis/statistical understanding: Experience structuring data to get the most accurate read
• Media Foundations: Beginning foundation of understanding media strategy, budget setting and channel selection
• Data Science: Experience applying more advanced analytics/statistics using code
  
  

Desired Technical Skills

• Strong proficiency with MS Excel, PowerPoint are a must
• Familiarity and beginning experience with
• 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 and application of one of the following
• Data visualization: tools such as Tableau, Datorama, Alteryx
• Advanced analytics software packages: SQL, R, Python or other
• Concepts of database design and SQL
  

Requirements

• Experience: 2-3 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, analytical fine arts, or business/marketing fields
  
  

Qualities (in Order Of Priority)

• Curiosity and Forward Thinking – A natural and persistent inclination to explore, discover, and learn, and a general fascination with analytics. The drive to go beyond asking “what?” to ask “why?”; a commitment to digging beneath the surfaces and interrogating information versus accepting it at face value.
• Collaboration – A desire to create a collaborative working environment where the notion of team comes before companies
• Adaptability, Flexibility and Resilience – A comfort with fast paced, intense, changing business and everything that comes with that. Client’s shift strategic direction incredibly fast, you must have a temperament that enjoys and reacts positively to change.
• Problem solving – An ability to figure out and solve problems on your own, leveraging all resources available.
• Creativity – A knack to think, solve problems in non-linear ways and connect dots to craft compelling stories.
• Confidence – A willingness to share opinions and present recommendations with conviction.
  
  

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

$45,000—$80,000 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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