Top Data & Analytics Jobs

Embed with Revenue leadership to identify high-value questions, build scalable analyses, models, and visualizations, and use AI agents and LLM tooling to accelerate insight delivery. Advise data teams on models, metrics, and semantic layers; validate AI-assisted outputs; communicate recommendations to technical and executive audiences; and develop reusable tooling and documentation.

Design and maintain production data pipelines and infrastructure (Databricks, Airflow), ensure data quality and governance, build rollups and consumable datasets, implement CI/CD and automated testing, create and maintain Looker dashboards, mentor team members, collaborate cross-functionally, and integrate AI tooling to enable self-service analytics and data-driven product decisions.

Lead client-facing analytics for beverage and emerging business units, delivering actionable insights, analytical products, and presentations to external stakeholders and senior leaders. Mentor teammates, manage complex projects, adopt new analytical capabilities, and contribute to cross-functional analytics initiatives.

Operate as the operational lead for measurement studies with third-party partners: manage study intake, validate campaign specs, track timelines, analyze sales lift and media KPIs, present results to clients, improve data delivery processes, and work cross-functionally to ensure clean execution and actionable insights for CPG advertisers.

Build and maintain production data pipelines, data foundations, and automation to enable product analytics. Collaborate with decision scientists and data teams to document, validate, and monitor event-based datasets, implement CI/CD and testing, and deploy alerting/anomaly detection to ensure reliable analytics data.

Analyze large behavioral and transaction datasets, build reports and dashboards, collaborate with product and engineering to inform data-driven product decisions, automate analyses, communicate insights to stakeholders, and brainstorm new data uses to improve user experience.

Lead and mentor a team of decision scientists to drive product strategy through analytics, experimentation, and measurement. Partner with product leads to prioritize initiatives, oversee end-to-end analytics projects, ensure statistical rigor in A/B testing, maintain event tracking quality, and deliver actionable insights using Databricks, Airflow, Python/R, Looker, and AI tooling.