Summary: This role involves building predictive models, automating data infrastructure, and delivering executive insights to directly influence sales strategy and resource allocation in a global organization. Highlights: 1. Shape global sales strategy and resource allocation 2. Leverage AI-native tools for custom apps and automation 3. Influence business operations and people outcomes with analytical output What the Candidate Will Do \- * Build predictive models and GTM frameworks \- account scoring, forecasting, quota modeling, and Book Building that directly shape where sellers focus and how leadership allocates resources across a global sales org. * Own high\-stakes analytical models \- build and maintain outputs where accuracy matters because they directly influence how the business operates and how people are measured, pressure\-testing assumptions and surfacing downstream impact before decisions are made. * Engineer automated data infrastructure \- replace manual workflows with scalable SQL pipelines, Python\-based automation, and ETL processes so the team scales without bottlenecks. * Deliver executive insights \- produce deep\-dive analyses and data products for MBRs, QBRs, and leadership reviews, translating complex data into clear narratives with actionable recommendations. * Multiply your impact with AI \- leverage AI\-native tools across your entire workflow to build custom apps, automate repetitive work, and move at startup speed within Uber. \- Basic Qualifications \- * Strong Experience using AI coding tools (Cursor, Claude Code, Copilot, or similar) as a core part of your workflow. * Preferably experience with SQL and Python for querying, data transformation, automation, and analytical modeling. * Demonstrated analytical problem\-solving ability\-you break down ambiguous problems, think in tradeoffs, and calibrate your rigor to the stakes. \- Preferred Qualifications \- * Experience in environments where your analytical output directly affects business operations and people outcomes\-and an appreciation for the precision and tradeoff\-thinking that responsibility requires. * Ability to build lightweight data applications (Streamlit, Flask, or similar) that move insights beyond static dashboards into interactive, self\-serve products. * Strong cross\-functional communication\-you present options with pros, cons, and who bears the impact so leadership makes informed decisions, not just fast ones. * Background in data analytics, BizOps, consulting, RevOps, or analytics engineering. No specific years required\-demonstrated ability and learning agility matter more than tenure.
Juan García
Indeed · HR
Juan García
Indeed · HR
