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.
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
- Knowledge of digital clean rooms, and their related concepts and strategy
- Certifications in any of the following: Meta (Blueprint), SQL, Python, R (online)
Responsibilities
- Partner with Planning & Investment teams to provide expert hands-on 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.)
- Leverage technical (coding) expertise 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
- Lead and train managers and other junior team members
Other
- Strong project management skills with an ability to set priorities, meet deadlines and know when to ask for help
- Advanced presentation and communication skills
- Some experience working with non-technical teams
- Demonstrated domain knowledge of business/industry
- A university degree in mathematics, computer science, statistics or related field, and 5-7 years of experience in informatics work in academia, advertising, management consulting, marketing or digital consulting
- This role is hybrid, requiring three (3) days per week in the office. The remaining two (2) days may be worked remotely.
