Top Tech Jobs & Startup Jobs in Los Angeles, CA

Design, develop, and maintain enterprise Power BI dashboards and reports. Integrate data from SQL Server, Azure, Excel and other sources, perform data modeling and DAX calculations, validate data, and document data models and reporting logic while partnering with business stakeholders.

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Own full-cycle sales for net-new Workday implementation deals globally: prospect, qualify, negotiate, and close high-value professional-services contracts while building C-level relationships and maintaining a high outbound activity pace.

Conduct data science research on experimental methodologies and causal modeling, develop tools to analyze experimental data, prototype improvements to platform features, and communicate results to internal teams and external stakeholders to drive product and research decisions.

The Product Manager will oversee data strategy and execution for Retrospective Risk Adjustment Coding products, managing data integration, database performance, and client onboarding for healthcare compliance.

Own full sales cycle for enterprise fleet, transit, and autonomous vehicle customers. Build outbound pipeline, negotiate contracts, close deals, collaborate with product and operations, contribute to sales playbook, and travel to customer sites and events (≈25%).

Full-cycle, revenue-carrying sales role focused on sourcing, winning, and expanding enterprise and mid-market creative partnerships. Own pipeline from outbound prospecting to close, lead discovery and pitch conversations with marketing leaders, collaborate with Creative Directors to build proposals, scope/pricing SOWs, and grow accounts into integrated long-term relationships across agency brands.

Lead and own incident response engagements: manage client communications, set strategy, direct technical workstreams, mentor team members, track budgets/SOWs, ensure timely containment, evidence preservation, log collection, and recovery guidance while identifying upsell opportunities and maintaining SLA deliverables.

Lead platform-wide product strategy and execution, own the roadmap, drive customer discovery with insurance brokers, work closely with engineering to ship features, define AI product strategy, synthesize cross-functional signals, set success metrics, and communicate decisions across the organization.

Own computer-vision accuracy end-to-end: measure per-customer metrics, investigate misclassifications, curate and label datasets, prioritize retraining, and build continuous learning pipelines. Partner with ML/CV engineers and stakeholders to define acceptance criteria, translate findings into actionable fixes, and eventually implement tooling and retraining to ship regular model improvements.