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 California: $90,000.00-$215,000.00 Omnicom’s policy requires employees to work in the office for a minimum of three days a week, unless additional in-office days are directed by their agency or manager. 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.