Data Scientist, Wpromote

• Degree in Computer Science, Engineering, Statistics, Economics, or any related quantitative discipline preferred
• M.S. + 2 years of experience or B.S. + 4 years of relevant experience
• Strong programming skills in R, Python & SQL
• Work experience within the digital advertising or MarTech field
• Demonstrable successes in delivering data-driven products, including being involved in all aspects of the product development life cycle
• A deep understanding of statistical modeling and machine learning techniques
• Experience solving complex optimization problems, preferably with reinforcement learning
• Strong working knowledge with large data sets, preferably in the digital marketing domain
• Experience with cloud OLAP database platforms such as BigQuery and Snowflake
• Strong communication skills, with both technical and non-technical audiences
• Ability to work beyond familiar algorithms - to get out of one’s comfort zone and earnestly seek to integrate the best solutions to business challenges
• Sincere interest in working towards the data-driven future of digital marketing within a fast-growing organization

Desirable

• We’re looking for a Product Designer to join our growing team and contribute to the design of Polaris, our AI-driven marketing platform
• Polaris helps businesses drive impactful results across media, creative, measurement, and audience through advanced AI built for expert marketers and clients to use directly
• In this role, you’ll work collaboratively with product management, engineering, and data science to design intuitive, elegant solutions that make sophisticated AI capabilities accessible and effective for our users
• Working closely with Product Development to identify high-impact business problems that can be solved by data science and machine learning methods
• Building always-on solutions to optimize ad spend on myriad digital platforms
• Developing multi-agent and hierarchical systems to improve multiple aspects of clients’ marketing performance
• Conducting incrementality tests and building Media-Mix Models (MMMs)
• Maintaining data science and machine learning workflows by fixing bugs or improving model performance if required
• Articulating complex, technical results and methods to internal stakeholders
• Occasionally join client meetings to understand client data problems and propose innovative solutions
• Design, develop, and deploy machine learning models and statistical analyses to solve complex business problems
• Build and maintain front-end applications or dashboards to visualize and operationalize model outputs
• Collaborate with back-end engineers to integrate APIs and ensure seamless data flow between models and applications
• Create interactive user interfaces (UIs) that effectively communicate insights and model results