Director, Data Science

Director, Data Science

Omnicom Media (OM), the media services division of Omnicom Group Inc. delivers transformational experiences for consumers, clients, and talent. Powered by the Omni marketing orchestration system, OM connects best-in-class capabilities that enable our full-service media agencies OMD, PHD, and Hearts & Science to deliver more relevant and actionable consumer experiences, more productive and proactive client experiences, and more collaborative and rewarding talent experiences for the more than 24,000 people serving the world's leading brands in OM agencies around the globe.

Team Overview

We are a team of engaged data-curious professionals who continuously seek new and improved ways to learn from our extensive data assets. We share ideas, code, outcomes, and credit for our collective efforts. We're looking for explorative, independent data scientists to grow with us as we tackle ever-changing challenges.

Position Overview

As a company, we serve as the foundational data and technology layer in which analytics and insights can be accessed through a single lens. Our main goal is to advance our clients' advertising and marketing strategies through the use of smart data and technology application that unlock insights and drive business results. Our unique approach to data and technology – one that relies on transparency, neutrality, and interoperability – allows us to deliver purpose-built and scalable solutions that make data actionable. We have teams of analysts, data and marketing scientists, consultants, and technical experts to help us meet the business goals of our clients.

Join our dynamic and diverse team – data solutions for marketers, by marketers.

Key Responsibilities

As a member of the Data Science team, you will work with agency strategists and media buyers to create solutions that shape the strategic direction of your client's marketing plans through data-driven insights, audience solutions, and measurement techniques.

This will involve

• Interacting with client and programmatic teams (internal agency and external) to plan & execute optimization strategies as well as test & measurement plans related to media performance
• Working with tech partners directly regarding data, clean rooms, custom bidding platform functionality, and troubleshooting related issues
• Working with data from ad servers, DSPs, measurement partners, and other online and offline datasets to develop client-specific solutions
• Collaboratively ideating and building tools that aid with analysis and ML transparency, visualization, and performance measurement

Required Skills And Qualifications

• 6+ years of industry experience; knowledge of ad-tech ecosystem, programmatic advertising, and agency work experience a plus
• Bachelor's degree in statistics, mathematics, economics, engineering, information management, social sciences, or business/marketing related fields
• Advanced quantitative degree or intensive bootcamp experience is preferred
• Must have hands-on expertise in Python; SQL proficiency preferred
• Experience with cloud computing platforms such as AWS or GCP
• Experience managing data scientists and end-to-end analytics projects
• Direct exposure to client media, marketing, and analytics teams

Our culture and working style within the group fosters a positive, productive, entrepreneurial team spirit. We demonstrate a strong working knowledge of media across all channels and are data driven in our approach. We use analytic and technical knowledge to identify the most effective strategies to address our clients' needs. We also work to stay sharp and up to date with our skills and trends in the marketplace that help us bring the best for our clients.

Compensation Range

$140,000 - $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.