Measured

Product Manager

• Lead as a highly proactive, influential, self-motivated and hands-on product management leader, owning multiple product initiatives simultaneously.
• Own product adoption and customer impact for assigned products, including activation, usage depth, customer feedback loops, in close partnership with Customer Success and Product Marketing.
• Own end-to-end lifecycle of specific products in alignment with customer needs, internal stakeholders, business goals, and technical feasibility.
• Create and maintain product backlogs, detailed product requirements, designs, documentation, data mappings, and customer feedback.
• Plan quarterly OKRs and monitor key performance indicators to evaluate product adoption and identify new growth opportunities.
• Identify potential risks in the product development lifecycle and proactively implement strategies to mitigate them.
• Proactively conduct market research, competitive analysis, and partner assessments to shape the product roadmap and identify integration opportunities.
• Champion user experience (UX) by collaborating with design teams to ensure products meet high standards of usability and customer satisfaction.
• Work with product marketing and sales to develop positioning and messaging that resonate with target markets, and provide training on product features and benefits.

Director, Product Management – Measurement

Full-stack Engineer

• Drive the technical roadmap for AI/ML systems, aligning model development and deployment initiatives with key business outcomes.
• Establish and champion scalable AI delivery practices (evaluation, deployment, monitoring, governance) and production-grade architecture patterns and engineering standards.
• Identify and address strategic technical debt and performance bottlenecks within the core AI/ML platform and inference services.
• Lead the adoption of emerging AI research, foundational models, and deep learning frameworks that future-proof our platform's intelligence capabilities.
• Build agentic workflows that can query metrics, run analyses, and cite supporting data
• Implement RAG patterns over internal schemas/data
• Establish an evaluation and guardrails framework: monitoring for drift/hallucinations, along with PII handling, tenant isolation, policy controls, and audit logging.
• Oversee production pipelines for AI services and ML workflows, including deployment, monitoring, and governance.
• Lead the development and evolution of scalable tools for prompt/agent versioning, experimentation, evaluation, release management, and monitoring.
• Ensure robust data validation, model testing practices, continuous integration/continuous delivery (CI/CD) for ML models, and automated deployment of AI services are in place.
• Promote engineering best practices for building explainable, ethical, and bias-aware AI systems through agile methodologies and continuous improvement.
• Build, mentor, and grow high-performing AI Engineering, Data Science, and AI Research teams and technical leaders.
• Partner with executive leadership to define and execute technical strategies for integrating AI across product lines and departments.
• Foster a culture of rigorous scientific experimentation, accountability in model performance, and cross-functional collaboration between research, data, and engineering.
• Serve as a senior technical advisor on complex AI/ML architectural decisions, providing guidance on model selection and influencing data product direction.
• Whatever else it takes to get the job done!

Principal Engineer, AI

Marketing

• Lead the end-to-end design, execution, and interpretation of geo tests and MMM projects
• Improve frameworks to account for evolving marketing realities: cross-border, CRM-driven, short-flight, and campaign overlap complexities
• Own statistical modeling architecture and ensure scientific rigor
• Conduct deep-dive analysis on test results and model outputs
• Isolate media drivers, identify patterns (e.g., PMax vs ASC differences), and provide “why behind the what”
• Deliver customer-facing narratives with clear business implications
• Support CS in interpreting test/model results and crafting recommendations
• Join key client calls, QBRs, and renewal discussions as the expert voice of measurement
• Help CS anticipate challenges and align on optimization actions
• Use Python, SQL, and statistical methods to process and analyze large-scale marketing datasets
• Build dashboards and reports to track campaign and channel-level performance
• Perform A/B testing, incrementality validation, and lift modeling
• Develop processes to help teams monitor, document, and report on ROI from campaign changes
• Partner with Product to integrate insights into customer-facing tools (e.g., Media Plan Optimizer)
• Evolve dashboards and test summaries for usability and clarity
• Recruit, mentor, and manage a team of analysts and data scientists
• Champion a culture of intellectual rigor, commercial thinking, and outcome orientation

Director, Marketing Science

Customer Support

• Build, lead, and design best-in-class customer support organization trusted by enterprise customers
• Deliver fast, accurate, and clear support that reinforces confidence in Measured’s data and platform
• Ensure onboarding and technical operations are designed to enable support excellence
• Reduce customer-impacting issues through prevention, automation, and systemic fixes
• Scale support quality without scaling human effort linearly
• Design, build, and scale a modern customer support function, including:
• - Support tiers and specialization models (L1/L2/L3)
• - Escalation frameworks and incident ownership
• - Support operating rhythms and quality standards
• Establish support as a trusted, high-credibility function for enterprise customers.
• Own all steady state support for customer facing GA products, including day-to-day issues and critical escalations.
• Ensure support responses balance speed, accuracy, and clarity, especially in high-stakes situations.
• Define and track support KPIs including CSAT, response time, resolution time, and repeat issue rates.
• Build robust internal knowledge bases, playbooks, and response standards.
• Ensure support teams are trained to clearly explain:
• - Platform behavior and outputs
• - Common data and integration issues
• - Incident impact and resolution paths
• Establish QA processes for support interactions to ensure consistency and correctness.
• Drive self-service where appropriate without degrading customer trust.
• Own technical onboarding and integrations to ensure customers start with clean, reliable setups.
• Define onboarding success criteria, exit gates, and clean handoffs into support.
• Reduce onboarding variability and early-life escalations through standardization and tooling.
• Ensure onboarding quality directly reduces downstream support burden.
• Own post-sales technical reliability, including monitoring, escalation coordination, and root-cause remediation.
• Act as the customer-facing owner during technical incidents, ensuring transparent communication and trust recovery.
• Partner with Engineering to eliminate recurring issues and operational debt.
• Own internal tooling and backend workflows that support onboarding and support execution.
• Identify and eliminate unnecessary manual work across onboarding and support.
• Drive automation and tooling investments that reduce support load without sacrificing quality.
• Track and improve operational leverage metrics (automation %, human hours per account).
• Ensure support and onboarding scale sustainably as customer volume and complexity grow.
• Serve as the primary voice of post-sales customer reality to Product and Engineering.
• Surface recurring issues, confusion patterns, and reliability risks with clear evidence.
• Partner with Product and Engineering to influence priorities that improve supportability.
• Ensure support readiness for new launches, features, and platform changes.
• Hire, develop, and retain high-performing support and technical operations leaders.
• Build clear career paths and expectations across support, onboarding, and technical specialists.
• Foster a culture of empathy, accountability, calm execution, and continuous improvement.
• Ensure stakeholders across the company trust this organization to deliver customer-critical outcomes.

Head of Customer Support – Technical Operations

Content Marketing Manager

• Own Measured’s content strategy and editorial roadmap, aligned to company priorities, pipeline goals, and category leadership.
• Define and evolve core content pillars (“tent poles”) and build full-funnel content journeys across awareness, consideration, and decision.
• Identify white-space topics and POVs where Measured can lead the market—not follow it.
• Serve as a strategic partner to executives and subject-matter experts to shape compelling narratives and points of view.
• Produce and oversee high-quality content, including:
• Short-form blogs (300–500 words)
• Deep, long-form pieces (900–2,000+ words)
• POV essays, bylines, customer stories, and research-driven content
• Translate technical concepts (incrementality, MMM, experimentation, attribution limitations) into clear, persuasive stories for senior audiences.
• Act as a strong editor—elevating clarity, argumentation, and credibility across all content.
• Partner with demand gen and web teams to ensure content is discoverable, distributed, and measurable.
• Own SEO-informed content planning, including keyword strategy, FAQs, and evergreen assets.
• Track content performance across engagement, pipeline influence, and downstream impact—not just traffic.
• Continuously optimize content based on performance data and audience insights.
• Collaborate closely with: Product & Data Science to ensure technical accuracy
• Sales & Revenue Marketing to support enablement and deal acceleration
• Comms & PR to amplify thought leadership externally
• Video & Events teams to extend content into multimedia and live formats
• Maintain a clear, well-run content calendar and production workflow across teams.
• Build scalable, repeatable content processes that balance speed, quality, and rigor.
• Manage competing priorities with strong judgment and clear communication.
• Take ownership, move proactively, and do what’s needed to deliver impact.

Director, Product Management – Measurement

Principal Engineer, AI

Director, Marketing Science

Head of Customer Support – Technical Operations

Senior Content Marketing Manager