What are the responsibilities and job description for the Director, Data Science position at Omnicom Media Group US PHD?
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.
Team Overview
At PHD, we provide our clients with powerful and innovative media strategies, along with big ideas that are driven by insights. PHD Data Scientists deliver analytic solutions across a wide variety of client applications and help brands to connect better with the customers. They process and integrate big data in data clean rooms from media advertising platforms including the first party and the third-party data and support business insights and growth solutions.
Our data scientists build advanced predictive models utilizing machine learning and advanced statistic. PHD data scientists leverage data to address various types of marketing challenges such as audience creation, segmentation, identifying audience journey, optimization, digital attribution, customer retention, customer behavior prediction, and cross channel customer experience.
The Data Science team is pivotal in the delivery of modern agency services. We are tightly integrated with marketing science teams to deliver on and exceed our clients' business goals.
Responsibilities
External facing responsibilities:
- Partner with Planning & Investment teams to provide expert hands-on and well as strategic Data Science support across the entire campaign lifecycle.
- Build advanced ML models to cluster and segment audiences, scale and deploy custom audiences across various platforms/ publishers
- Run descriptive and diagnostic analyses to help measure campaign performance within clean rooms and/or other analytics platforms (e.g., Google ADH, Facebook advanced analytics, Amazon Marketing Cloud, etc.)
- Help develop strategic analytical roadmaps to institutionalize data driven outcomes
- Excellent project management skills with an ability to set and achieve goals, meet deadlines and act with a strong sense of urgency without compromising executional excellence
- Leverage technical (coding) expertise to help bring about process efficiencies
Internal facing responsibilities:
- Build and present decks that provide a compelling narrative to decode complex analytical results to technical and non-technical audiences
- Help design and develop the DS practice knowledge repository and delegate tasks to junior resources to support vision
- Lead and train direct reports and manage their career progression
Required Skills
- Hands-on programming language skills (SQL, Python, R, etc)
- Experienced in machine learning techniques, causal models, etc. to support the analysis of information
- Advanced presentation and communication skills
- Experience working with non-technical teams
- Clear understanding of digital clean rooms, and their related concepts and strategy
- Certifications in any of the following: Meta (Blueprint), SQL, Python, R (online)
- Expert-level domain knowledge of business/industry
Education and Experience
- A university degree in mathematics, computer science, statistics or related field, and 7-10 years of experience in informatics work in academia, advertising, management consulting, marketing or digital consulting
- Knowledge of agency-side execution process is desirable, but not required
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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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