• Delivered cross-functional leadership across product management and data analytics, building the product intelligence ecosystem by creating a multi-year vision and strategy for data culture and infrastructure change.• Steered roadmap development to evaluate and monitor software as a service (SaaS) product growth; tracked 10 key metrics across multiple dimensions, including adoption, engagement, and retention.• Fostered and maintained an environment focused on data-driven decision-making by orchestrating the design of a diverse array of analytics products within relational and resource description framework (RDF) models.• Instrumental in securing the company's largest contract ever at $9M total by providing product analytics to the sales team; launched five new analytics products, leading to increased user adoption of the analytics platform.• Successfully reduced time-to-insight by 50% by optimizing and streamlining data processes and infrastructure upgrades; installed two new data management features that reduced delivery time.• Launched a data infrastructure enhancement project to establish a data catalog for governance and to conduct two proofs of concept to evaluate data virtualization and a product knowledge graph.

• Founded and spearheaded a high-performing analytics team of 20 to enable data-driven decision-making and operational excellence; successfully generated $1M+ cost savings and 4,000+ annual hours saved.• Created machine learning models using Python in Domino Data Lab, including software profile recommender, incident classification, clustering, and natural language processing (NLP) to retire 2,500 knowledge articles.• Conducted data analysis to produce and present key insights to executive leadership and established actions to achieve service delivery target goals; produced real-time insights to prepare business processes for automation.• Promoted performance improvement and optimization by building cross-unit knowledge-sharing forums and technical working groups; assessed team capabilities and led goal setting to advance two maturity levels.• Created the analytics business plan and strategy to ensure alignment between operations and strategy; developed processes for data engineering, requirements engineering, business intelligence, and data governance.