Manager, Data Science

Company Description

Spark Foundry is a global media agency that exists to bring HEAT – Higher Engagement, Affinity, and Transactions – to brands. By combining flawless media fundamentals with aggressive innovation, Spark inspires consumers to pay more attention; to care more about our clients’ brands; and to buy more products and services from them.

Balancing the nimble spirit of a startup with the powerhouse soul of Publicis Media, Spark Foundry delivers the best of both worlds to a client roster that spans some of the world’s best and most beloved brands and companies. We combine boutique-caliber insights and service with the buying clout and first-look access of a global leader, bringing the heat to challenger brands that want to act like giants, and to giant brands that want to act like challengers.

With a bottom-up culture that celebrates diversity and aims for all voices to be heard, Spark has become a magnet for the industry’s best talent, with one of the best retention rates in the industry. And by applying a whole-person approach to professional and personal development, Spark develops a workforce that is well prepared for today’s challenges, and also poised to create meaningful careers in the years to come.

Because we know that heat arises the intersection of complementary forces, our professionals come from myriad disciplines and backgrounds: data, analytics, and insights; content and creative production; communications and strategy; finance and marketing; and sociology, psychology, and other liberal arts disciplines.

Overview

The Manager of Data Science is responsible for supporting advanced audience development and data and technology enablement to drive client growth. This role is both strategic and hands-on, working with large individual- and transaction-level datasets to design and deliver best-in-class data science solutions that enable clients to identify, target, engage, and measure audiences with precision and efficiency. The data scientist must be able to translate across technical and non-technical collaborators in both directions: from client requirements to innovative data science solutions, and from quantitative results to business-relevant, actionable insights.

Responsibilities

• Navigate a complex, multi-source data environment and creatively identify appropriate datasets and methodologies for ever-changing client questions

• Monitor data quality and maintain data science pipelines for client data assets, including 1PD and 3PD

• Develop, deploy, and maintain ML and AI workflows for identifying and targeting relevant audiences, including propensity/classification models as well as unsupervised clustering/segmentation

• Develop and execute novel methods of analyzing audiences, such as customer profiling, customer journeys, purchase predictions/recommendations, etc.