Manager, Data Science

Omnicom Media Group US H&S•New York, NY

6d•$95,000 - $105,000•Hybrid

About The Position

Hearts & Science has been inspired by confident marketers seeking business advantage in a world of personalized digital marketing, where CRM and addressable channels converge, and decisions must be made in real time to aggregate effective reach and deliver the right message at the right time. Designed to inform brand strategies with real-time insights, Hearts & Science is a data-driven marketing agency with expert media planning and buying capabilities, among other services that include shopper marketing, marketing innovation and content activation. 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.

Requirements

Hands-on programming language skills (SQL, Python, R, etc)
Intermediate exposure to machine learning techniques, causal models, etc. to support the analysis of information
Advanced presentation and communication skills
Some experience working with non-technical teams
Knowledge of digital clean rooms, and their related concepts and strategy
Certifications in any of the following: Meta (Blueprint), SQL, Python, R (online)
Demonstrated domain knowledge of business/industry
A university degree in mathematics, computer science, statistics or related field, and 3-5 years of experience in informatics work in academia, advertising, management consulting, marketing or digital consulting

Nice To Haves

Knowledge of agency-side execution process is desirable, but not required

Responsibilities

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.)
Adhere to set deadlines and ensure high quality work product
Leverage technical (coding) skills to help bring about process efficiencies
Contribute to building decks and reports that help translate analytical results to internal and client teams
Contribute to building DS Practice knowledge repository via decks, documents and other artifacts