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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Manager, Data Science - **Company:** Publicis Groupe - **Location:** New York, NY, United States - **Experience:** Experienced - **Salary:** $125,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Big Data, BigQuery, Cloud Computing, Profiling, Code Reuse, Python (Programming Language), Machine Learning, SQL Databases, Systems Integration, Snowflake, Data Strategy, Git, Data Management, Amazon Redshift, Databricks - **Published:** July 15, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=2edb694c869728a0 ## About the Role 2+ years of data science experience in advertising, marketing, or related fields, with agency experience preferred * Advanced degree in Statistics, Data Science, or other quantitative fields preferred * 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 cloud-based big data platforms, e.g. Snowflake, BigQuery, Redshift * Experience building agentic workflows and integrating AI solutions into existing data and tech stacks ## Description The Manager of Data Science is responsible for leading 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. * 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, including client-facing discussions and dashboards * Collaborate with analytics teams to develop and implement testing frameworks for closed-loop audience measurement * Develop and implement a test-and-learn roadmap to continuously refine data-driven strategies, enabling rapid optimization * 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 * Independently set, communicate, and deliver against realistic expectations and timelines * Guide the development of client data strategy and promote the adoption of data-driven processes across planning, activation, and measurement * Proactively identify and pursue new use cases and opportunities to use data science capabilities to solve client challenges ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Making Data Warehouses fast. 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