The posting
LiveRamp is shaping the future of responsible data collaboration between the world’s leading brands, retailers, financial services providers, and healthcare innovators. As consumers embrace new AI-driven experiences, the LiveRamp data collaboration network exponentially expands the breadth and accuracy of the data on which marketing AI capabilities operate, powering deeper customer insight and measurable performance on a global scale. LiveRamp is headquartered in San Francisco, California, with offices worldwide. Learn more at LiveRamp.com.
Your team will:
- The Business Technology team helps LiveRamp solve complex operational problems by connecting strategy, process improvement, technology, data, and change management.
- The team works across functions to understand how work is performed today, identify practical opportunities to improve it, and support measurable adoption of better ways of working.
- Serve as an enablement and delivery partner that owns standards, governance, shared engineering capacity, tool evaluation, observability, process discovery, and delivery
- The team provides a single, structured path from opportunity discovery and intake through prioritization, governed design, delivery, measurement, and scale.
- You will collaborate with technology teams and business partners on initiatives such as operating-model improvements, workflow redesign, systems and tool rationalization, automation opportunities, data and reporting enhancements, and employee-experience improvements, including AI and agentic use cases across Commercial, Finance, Customer Engagement, and Corporate Operations
- You will work closely 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.
- Your work will help turn ambiguous business challenges into structured plans, informed decisions, scalable AI-enabled workflows, and measurable outcomes.
You will:
- Partner with Business Technology (IT), the AI Center of Excellence, business leaders, and cross-functional stakeholders to identify, prioritize, and deliver AI-enabled, cross-functional transformation initiatives that improve operating efficiency, employee experience, and measurable business outcomes.
- Cross-functional process re-engineering. Map current-state processes, systems, data flows, and decision points across Commercial, Finance, and Customer Engagement; identify what to disrupt, simplify, standardize, or automate.
- Requirements translation. Translate business needs into clear requirements, future-state process designs, user stories, and success measures
- Identifying and turning opportunities into scoped, buildable agentic solutions for the engineering resources within your team.
- Executive partnership. Own the relationship with business stakeholders; facilitate workshops and working sessions that align leadership stakeholders on problems, options, and decisions.
- Value quantification. Establish baselines and success metrics, and track realized value against agreed criteria (cycle time, cost avoidance, productivity, quality).
About you:
- 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-state 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 stakeholders, including Director level and above, across business and technology teams to facilitate decisions and deliver outcomes; comfortable establishing clear ownership when accountability spans multiple 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 whether an initiative achieved its intended results; comfortable 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; able to maintain audit-ready governance and delivery documentation.
- Working knowledge of how AI, automation, data, and enterprise integrations can change business processes, including the limitations and risks of AI-enabled solutions.
- Comfort collaborating with Responsible AI, privacy, security, legal, compliance, data-governance, engineering, and finance stakeholders throughout the delivery lifecycle.
- Bachelor’s degree in business, information systems, engineering, economics, analytics, or a related field, or equivalent practical experience.
Preferred Skills:
- 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.
The approximate annual base compensation range is $116,500 to $170,500. The actual offer, reflecting the total compensation package and benefits, will be determined by a number of factors including the applicant's experience, knowledge, skills, and abilities, geography, as well as internal equity among our team.
We use automated decision systems (ADS) as part of our recruitment and hiring process. If you require an accommodation or believe that the use of an ADS may create a barrier to your application or participation in the hiring process due to a disability or other protected characteristic, please let us know. We are committed to providing reasonable accommodations and ensuring an equitable hiring experience for all candidates.
To all recruitment agencies: LiveRamp does not accept agency resumes. Please do not forward resumes to our jobs alias, LiveRamp employees or any other company location. LiveRamp is not responsible for any fees related to unsolicited resumes.
