- Provide thought leadership to executives and partners for select clients, ensuring success of complex projects across Customer Experience (CX), tracking meaningful KPIs, applied Machine Learning (ML) products, and data privacy compliance.

- Launched user-facing ML products for search & rank, personalization and other use cases with integrated teams of data scientists, data engineers and full-stack developers that increased customer engagement and direct revenue from site traffic- Championed optimized data architectures that leverage an appropriate balance of streaming, REST APIs, and batch processing to support use cases in product engineering, data lake ETL pipelines, and product analytics- Drove meaningful and operational business analytics with matrixed representation, distributed data governance, and automated reporting and alerting- Engaged a multi-tiered, fully remote and international workforce with personalized coaching, development and goal-setting

- Championed process improvements and Agile best practices to provide rapid, interactive improvements in analytic visibility and to improve data-driven business decision making- Architected event-based streaming strategies that enabled production product releases incorporating consumer-facing machine learning models - Introduced cross-department data governance and management processes to ensure secure, private and ethical handling of personal and private data and reduce financial/legal risk- Provided technical and architectural input to product roadmaps and feature requirements, ensuring project feasibility and reducing both project risk and time to impact- Maintained enterprise data architecture roadmap and implementation plan to optimize data science, machine learning, and business intelligence deliverables

- Standardized service offerings and introduced repeatable project management strategies that reduced project delivery risk, increased client-identified ROI, and reduced operating costs up to 20%- Coached and developed analytic delivery managers and directors to integrate data science and ML capabilities that increased multi-year client renewals and grew year-over-year client commitments- Recruited analytic, data science and data engineering resources in support of current and future project demands, providing the organization with new capabilities in providing data integrations, analytic strategies, and staff augmentation- Enforced standard data management and engineering practices that increased on-time delivery rates and increased resource utilization rates, resulting in organizational profit margins up to 65%- Promoted thought leadership marketing with published content, speaking engagements, and other public/private client events to increase sales lead generation, to address prospects’ concerns, and to reduce time to close

- Drove collaboration within integrated team of data scientists and full-stack engineers- Orchestrated alpha and beta release programs to test prototype viability and improve client feedback cycles, resulting in improved client engagement and satisfaction and in more viable product designs- Coordinated with patent lawyers and USPTO to support and grow company’s portfolio of intellectual property, filing two new patents and supporting increased company valuation in investment and fundraising- Promoted thought leadership marketing with published content, speaking engagements, and other public/private client events to increase sales lead generation, to address prospects’ concerns, and to reduce time to close

- Reframed the Agile SDLC processes around CI/CD frameworks with integrated quality assurance checks, allowing for scheduled releases to increase from quarterly to monthly while also reducing UAT test cycles 80%, critical bugs 65% and product performance escalations 35%- Introduced innovative data storage and processing techniques to core product capabilities, thereby meeting users’ performance expectations and reducing operating expenses during stages of significant growth- Re-architected application to REST microservices framework, enabling the engineering team to migrate from unsupported legacy vendors to JavaScript framework and to improve UI/UX- Recruited data science talent to introduce advanced analytic and machine learning capabilities, resulting in a product roadmap that proved critical in closing new sales and raising capital