Lead Business Transformation Partner

LiveRamp•San Francisco, CA

1d•$116,500 - $170,500

About The Position

The Business Technology team connects strategy, process improvement, technology, data, and change management to address complex operational problems across LiveRamp. It serves as an enablement and delivery partner, owning standards, governance, shared engineering capacity, tool evaluation, observability, process discovery, and delivery. The team provides a structured path from opportunity discovery and intake through prioritization, governed design, delivery, measurement, and scale. The role partners with technology teams and business functions on operating-model improvements, workflow redesign, systems and tool rationalization, automation, data and reporting enhancements, and employee-experience improvements, including AI and agentic use cases across Commercial, Finance, Customer Engagement, and Corporate Operations. It works with AI engineers, data and platform teams, AIOps/DevOps, Security, Legal, Privacy, Finance, and business process owners to ensure solutions are useful, secure, governed, measurable, and production-ready. The position turns ambiguous business challenges into structured plans, informed decisions, scalable AI-enabled workflows, and measurable outcomes.

Requirements

8+ years of experience in business analysis, management consulting, corporate transformation, operations, process improvement, program management, or a related field.
Experience gathering requirements and translating business needs into documented processes, user stories, functional requirements, or implementation plans.
Experience analyzing current- and future-state processes and identifying opportunities to improve efficiency, quality, controls, or customer and employee experience.
Experience redesigning end-to-end, cross-functional processes and translating opportunities into prioritized initiatives, business cases, and delivery roadmaps.
Experience working with Director-level and more senior stakeholders across business and technology teams to facilitate decisions and deliver outcomes; able to establish clear ownership across functions.
Ability to structure ambiguous problems, define assumptions, evaluate options, and communicate clear recommendations.
Ability to use data to establish baselines, measure performance, and assess initiative results, connecting adoption, operational metrics, cost, and business value.
Ability to manage multiple workstreams, dependencies, risks, and deadlines in a changing environment.
Experience documenting workflows, operating procedures, process maps, decision logs, and other transformation artifacts, with the ability to maintain audit-ready governance and delivery documentation.
Working knowledge of how AI, automation, data, and enterprise integrations can change business processes, including limitations and risks of AI-enabled solutions.
Comfort collaborating with responsible AI, privacy, security, legal, compliance, data-governance, engineering, and finance stakeholders throughout delivery.
Bachelor’s degree in business, information systems, engineering, economics, analytics, or a related field.

Nice To Haves

Experience supporting enterprise-wide transformation initiatives or working across multiple departments, including Commercial, Finance, and Operations.
Experience with workflow automation, artificial intelligence, agentic workflows, low-code/no-code platforms, systems integration, or enterprise applications.
Familiarity with process-mapping, process-discovery/process-mining, value-stream mapping, and project-management tools.
Experience developing business cases, benefits-realization plans, KPI frameworks, or executive dashboards; experience measuring AI ROI, unit cost, capacity impact, or value by use case is especially valuable.
Familiarity with AI lifecycle management, experiment-to-production stage gates, safety evaluations, model/prompt or asset registries, monitoring, incident management, and retirement decisions.
Familiarity with AI observability and FinOps concepts, including token/model consumption, spend attribution, prompt quality, adoption or fluency measurement, and cost optimization.
Familiarity with governed data products, semantic layers, data lineage, access controls, data quality, and preparing structured and unstructured data for AI and retrieval use cases.
Experience with responsible AI, privacy, security, risk, compliance, data ethics, audit evidence, or governance-by-design practices.
Experience with organizational change management, communications, training, or adoption planning; experience creating role-based AI enablement, playbooks, communities of practice, or citizen-builder support.
Familiarity with Agile, Lean, Six Sigma, or other structured improvement methodologies.
Experience evaluating AI tools or vendors using structured criteria such as functionality, integration, scalability, security, performance, cost, support, customization, and vendor stability.

Responsibilities

Partner with Business Technology (IT), the AI Center of Excellence, business leaders, and cross-functional stakeholders to identify, prioritize, and deliver AI-enabled transformation initiatives.
Map current-state processes, systems, data flows, and decision points across Commercial, Finance, and Customer Engagement, identifying opportunities to disrupt, simplify, standardize, or automate.
Translate business needs into requirements, future-state process designs, user stories, and success measures.
Identify opportunities and scope buildable agentic solutions for the team’s engineering resources.
Own relationships with business stakeholders and facilitate workshops and working sessions to align leadership on problems, options, and decisions.
Establish baselines and success metrics, and track realized value against agreed criteria such as cycle time, cost avoidance, productivity, and quality.
Redesign end-to-end cross-functional processes and translate opportunities into prioritized initiatives, business cases, and delivery roadmaps.
Manage multiple workstreams, dependencies, risks, and deadlines in a changing environment.
Document workflows, operating procedures, process maps, decision logs, and other transformation artifacts, maintaining audit-ready governance and delivery documentation.
Collaborate with responsible AI, privacy, security, legal, compliance, data-governance, engineering, and finance stakeholders throughout the delivery lifecycle.