Sr. Director, Value Creation Insights

Accountabilities:: Lead the global Value Creation Insights organization, managing approximately 30 team members across analytics, value creation, marketing insights, financial analytics, analytics engineering, and AI-enabled analytics while establishing consistent standards across onshore and offshore teams. Own revenue forecasting analytics, including forecasting models, methodology, variance analysis, reconciliation, and the identification and remediation of assumption gaps in partnership with FP&A and Finance. Lead the development and governance of demand-generation reporting, establishing trusted sources of truth for funnel performance, opportunity stages, top-of-funnel metrics, marketing pipeline KPIs, and other commercial measurements. Oversee the development and evolution of predictive scoring capabilities, including product-fit scoring, propensity-to-buy models, ideal customer profile scoring, and customer health metrics, ensuring models are aligned with business objectives and actively adopted by Marketing, SDR, and Sales teams. Drive the operationalization of analytical models by embedding scoring, prioritization, insights, and recommendations directly into go-to-market workflows rather than treating analytics as standalone reporting. Lead the analytics engineering function across Fivetran ingestion, dbt modeling, Snowflake architecture, commercial data pipelines, data quality, and access governance, while managing integrations with sources such as Salesforce, Gong, Google Ads, Marketo, and other commercial platforms. Own governance for third-party commercial data sources and core metric definitions, ensuring consistent calculation logic for funnel stages, scoring inputs, forecasts, and company-wide KPIs. Partner with Data Platform Engineering on infrastructure strategy, capacity planning, modernization initiatives, and the transition from legacy BI environments toward a modern semantic and conversational analytics layer. Define and execute the team's AI roadmap across forecasting, scoring, and commercial analytics, identifying opportunities for LLM-powered insights, conversational analytics, automated workflows, and agentic solutions that create measurable business value. Design and deploy AI agents within Sales, Finance, and go-to-market workflows, including automated account and deal insights, forecast variance alerts, scoring explanations, and other decision-support capabilities, with clear standards for accuracy, governance, security, and adoption. Evaluate build-versus-buy decisions for AI and analytics technologies, balancing speed, cost, security, scalability, and long-term flexibility while providing clear recommendations to senior leadership. Act as a trusted analytics advisor to senior executives, translating technical findings into concise business narratives and presenting forecasts, insights, and strategic recommendations to VP and C-suite stakeholders. Establish cross-functional alignment around OKRs, MBOs, performance metrics, and other measurement frameworks while maintaining a formal operating model with FP&A that provides leadership with a consistent analytical foundation. Develop team operating practices covering prioritization, sprint cadences, stakeholder intake, documentation, peer review, coding standards, modeling methodologies, and reproducibility. Identify high-value analytical opportunities proactively, lead complex organization-wide data transitions and knowledge transfers, and ensure analytical initiatives progress from problem definition through adoption and measurable business impact. Represent AI-enabled analytics initiatives in broader AI and automation forums, bringing relevant emerging technologies, patterns, opportunities, and risks back into the team's strategic roadmap. Requirements: 10+ years of experience in analytics, data science, data engineering, or a closely related discipline, including at least 4 years of people management experience. Deep expertise in Snowflake, SQL, dbt, and modern data-stack technologies, with experience using platforms such as Omni, Power BI, Hex, or comparable BI and semantic-layer solutions. Hands-on experience with LLM-powered analytics, conversational analytics, AI agents, or automated workflows built on governed data models, with the ability to distinguish practical business value from experimental AI use cases. Proven experience building and managing distributed teams that combine onshore and offshore talent across multiple time zones while maintaining quality, security, accountability, and strong stakeholder relationships. Strong understanding of statistical modeling, predictive analytics, machine learning concepts, and their practical application to commercial and go-to-market use cases. Demonstrated ability to lead complex, multi-stakeholder analytical initiatives from problem framing and technical development through business adoption and measurable outcomes. Strong executive presence and communication skills, with the ability to translate sophisticated technical and analytical outputs into clear, actionable narratives for senior leadership. Strong commercial and SaaS business-model knowledge, including ARR, GRR, NRR, bookings, revenue recognition, forecasting, and go-to-market funnel mechanics. Proven ability to influence senior stakeholders across Sales, Marketing, Finance, Revenue Operations, and other business functions while building consensus around data-driven decisions. Experience working with Salesforce data, CRM analytics, marketing automation platforms, and commercial data ecosystems is highly desirable. Strong organizational and leadership skills, with experience setting team priorities, developing talent, establishing operating models, and maintaining high technical and analytical standards. Demonstrated curiosity and practical experience with emerging AI technologies, with the ability to incorporate AI into everyday business challenges, improve team efficiency, and identify new opportunities for analytics innovation. Benefits: Competitive compensation package, with eligibility for performance-based bonuses depending on role and location. Paid time off and paid parental leave. Location-dependent healthcare and wellness benefits, including medical, life, and disability insurance. Opportunity to lead a globally distributed analytics organization at the intersection of commercial strategy, data engineering, predictive modeling, and AI. Exposure to senior executive stakeholders and high-impact, organization-wide strategic initiatives. Opportunities to shape AI-enabled analytics capabilities, modernize business intelligence infrastructure, and introduce conversational analytics and intelligent automation into core workflows. Inclusive workplace environment with employee-led resource groups supported by senior leadership and executive sponsors.