Manager, Data Science
$88.54k - $141.69kPublicis Groupe Holdings B.V
Company description Spark Foundry was built during the most transformative time in the history of advertising and marketing. We deliver everything a traditional media agency has to offer and have grown into one of the world's most successful agencies by helping brands evolve their marketing by leveraging identity, commerce, artificial intelligence, and more to connect with people. Transformation is part of our DNA. Spark Foundry's start-up spirit delivers high-touch approaches and a never-ending desire to challenge the status quo. Combined with Publicis Media's powerhouse soul leveraging connected data assets, advanced AI applications, and investment clout, we "Bring HEAT to Brands." No other agency possesses the expertise that we do to address today's most pressing challenges to drive business transformation through media.
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 stakeholders in both directions: from client requirements to innovative data science solutions, and from quantitative results to business-relevant, actionable insights.
Responsibilities
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 stakeholders 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.
- Collaborate with strategy teams to translate technical outputs into relevant business insights and recommendations that can be surfaced in a variety of settings, from client-facing discussions to dashboards
- Collaborate with analytics teams to develop and implement testing frameworks for closed-loop audience measurement
- Implement a test-and-learn agenda to continuously refine data-driven media tactics, enabling rapid optimization
- Proactively identify and pursue opportunities for developing new capabilities, demonstrating end-to-end project ownership from ideation through deployment
- Contribute to data science team- and practice-building initiatives, e.g. presenting case studies in cross-functional forums, creating collateral around data capabilities, and pursuing internal research projects
- Document and share optimized, reusable code with data science colleagues using Git
- Continuously innovate, staying current with the latest technological developments and applying them to current workflows
- Deliver timely, accurate outputs aligned with client- and agency-defined best practices
- 3+ years of data science experience with consumer data; marketing agency experience preferred
- Degree in Statistics, Data Science, or other quantitative fields
- Deep theoretical and practical understanding of statistical/ML techniques and experimental design
- Hands-on experience with granular, disaggregated data, particularly behavioral consumer datasets and/or media logs; engagement with publisher walled gardens (AMC, ADH, etc.) a plus
- Advanced proficiency with SQL for big data analytics and Python for production-ready workflow development
- Experience with Databricks or similar platforms, e.g. Snowflake, BigQuery, Redshift
- Experience building agentic workflows and integrating AI solutions into existing data and tech stacks
Vacancy posted 2 days ago
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