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Build and lead Vibe’s Marketing Science function, defining measurement strategy and frameworks for incrementality, lift studies, attribution, and marketing mix modeling. Partner with Product, Data Engineering, Sales, Client Success, clients, and measurement providers to ensure statistically rigorous performance reporting. Analyze SQL data, design experiments, resolve discrepancies, present recommendations to senior stakeholders, publish insights, and build a team of analysts and managers.

Own the people agenda for France, Europe, and Asia, partnering with technical leaders across engineering and product. Lead employee relations and French labor law compliance, coach managers, advise on organizational design, build career frameworks, and adapt people programs including rewards, performance, and mobility. Support the full talent lifecycle across a rapidly scaling international organization.

As a Senior Backend Software Engineer, you'll enhance Vibe's bidding and pacing systems, lead the distribution of system knowledge within the team, and innovate within the audience streaming advertising domain, ultimately driving measurable improvements in performance metrics.

Own and operate production reporting pipelines: implement schema changes, move and transform tables, ensure accurate advertiser reporting, troubleshoot discrepancies, and collaborate with Data Platform to flag scaling or data-quality risks.

Own and scale Vibe's identity stack: design pipelines, improve clustering to resolve users/households from event data, operate production ML services at US scale, manage cost/performance tradeoffs, run end-to-end projects, and partner cross-functionally to deliver identity-resolution tooling.

Lead data engineering efforts, manage data governance, ensure compliance, and oversee data platform economics while designing scalable systems.

Lead the Identity squad to design, implement, and scale identity resolution (clustering/entity resolution) pipelines and algorithms at US scale. Own architecture, cost/performance optimization across Dagster, Spark, and Iceberg, build observability and evaluation frameworks, extend identity into audience construction, and lead cross-functional roadmap and mentoring for the squad.

Own and productionize the prediction stack for CTV performance advertising: design multi-task models, feature engineering from raw signals and identity graphs, train and deploy deep learning models, monitor drift, and optimize for measurable advertiser KPIs in collaboration with performance engineers.

Design, build, and operate data infrastructure to process massive event volumes into reliable, low-latency analytics and data products. Own real-time and batch services, platform tooling, observability, cost and performance optimization, on-call incident response, and cross-team stakeholder collaboration to enable analytics, ML, and reporting at scale.