Senior Analyst, Optimization – Paid Media Experimentation

Universal Orlando•Orlando, FL

About The Position

The Senior Analyst, Paid Media Experimentation is responsible for the end-to-end design, execution, measurement, and reporting of paid media experiments across Universal Destinations & Experiences, supporting UOR, USH, and new ventures. The role combines deep paid media platform expertise with experimentation, audience strategy, advanced analytics, and financial measurement capabilities to identify and size opportunities, design and execute technically sound experiments, evaluate incremental business impact, and translate results into actionable media and investment decisions. The Senior Analyst serves as a subject matter expert on paid media experimentation, with a strong understanding of how platform algorithms, campaign structures, targeting and segmentation, bidding strategies, attribution methodologies, and measurement limitations affect test design and results. This role partners across Paid Media, Strategy, Analytics, agencies, platforms, and cross-functional teams to prioritize the testing backlog, activate high-impact tests, and scale learnings across destinations and channels.

Requirements

Deep knowledge of paid digital media and hands-on expertise with Meta and Google advertising platforms, including campaign activation, targeting, optimization, experimentation, and measurement.
Strong understanding of audience strategy and segmentation, including first-party, modeled, affinity, intent, retargeting, prospecting, geographic, and platform audiences; audience sizing and overlap; suppression strategies; and the implications of audience construction on test validity and media performance.
Strong knowledge of experimentation methodology, including hypothesis development, A/B testing, holdouts, campaign and geo splits, test/control design, incrementality, statistical significance, success criteria, and experimental validity.
Demonstrated ability to independently design, execute, monitor, analyze, and communicate paid media experiments across multiple channels and platforms.
Strong analytical and reporting capabilities with experience using Looker dashboards and other analytics/reporting tools to analyze media and business performance.
Ability to translate test performance into financial impact, including revenue, EBITDA, savings, and addressable opportunity, and use expected value to inform prioritization and scaling decisions.
Deep understanding of how platform algorithms, bidding strategies, campaign structures, attribution methodologies, audience selection, optimization objectives, and automated platform changes can influence experimental outcomes.
Ability to reconcile and appropriately interpret differences between platform-reported metrics and enterprise/business measurement.
Strong QA and attention to detail when validating audiences, campaign configurations, creative, tracking, traffic allocation, and experimental setup.
Ability to translate complex technical and analytical concepts into clear recommendations for business and executive stakeholders.
Strong cross-functional partnership skills with demonstrated ability to work across Media, Strategy, Analytics, Creative, Legal, agencies, media platforms, and technical teams.
Ability to manage multiple concurrent experiments across platforms, destinations, and stakeholders in a deadline-oriented environment.
Bachelor's degree in Marketing, Analytics, Data Science, Statistics, Economics, Business, Communications, or a related field required; or equivalent combination of education and experience.
5+ years of experience in paid media, media analytics, experimentation, digital marketing analytics, or a related discipline.
Hands-on experience with Meta and Google advertising platforms and demonstrated understanding of campaign setup, audience targeting and segmentation, optimization, measurement, and reporting required.

Nice To Haves

Experience designing, executing, and measuring controlled paid media experiments strongly preferred.
Experience translating media performance into financial/business impact and working with Looker or comparable business intelligence tools preferred.
Experience supporting multiple brands, markets, destinations, or business units and working with agency partners preferred.

Responsibilities

Own measurement and reporting for paid media experiments, evaluating performance against the approved hypothesis, KPIs, success criteria, and business objectives.
Analyze test/control performance across spend, revenue, ROAS, CVR, CTR, CPC, CPM, AOV, conversions, EViV/CpEViV, and other relevant metrics to determine incremental impact, statistical significance, efficiency, and key performance drivers.
Use Meta, Google, Looker dashboards, and enterprise data and reporting sources to monitor performance, validate results, investigate anomalies, and develop executive-ready test readouts.
Understand and account for differences between platform-reported results and enterprise measurement methodologies, including attribution windows, optimization behavior, audience delivery, and platform-specific reporting nuances.
Quantify realized financial impact by applying observed performance lift to addressable audiences and media investment and calculating revenue, EBITDA, savings, and other business outcomes to inform scaling decisions.
Develop and maintain standardized impact-sizing methodologies and tools that translate test results into defensible at-scale financial opportunities for business and Finance review.
Analyze results across audiences, segments, placements, creative, platforms, destinations, and markets to identify performance drivers and determine where learnings can be scaled or require additional testing.
Translate complex results into clear recommendations for campaign optimization, audience strategy, creative strategy, media investment, scaling, or future experimentation.
Own the end-to-end execution of paid media experiments from approved hypothesis through launch, live monitoring, completion, and documentation.
Maintain advanced working knowledge of Meta, Google Ads/SA360, paid search, paid social, display/programmatic, CTV/OLV, and other applicable media platforms, including campaign structures, experimentation capabilities, audience tools, bidding and optimization algorithms, attribution settings, and reporting limitations.
Translate approved test designs into detailed execution briefs defining audiences, creative, campaign configuration, measurement requirements, dependencies, responsibilities, and timelines.
Build or coordinate test audiences and segmentation, including first-party, modeled, affinity, intent, retargeting, prospecting, geographic, and platform audiences; validate suppression, overlap, test/control allocation, and scalability.
Coordinate execution across internal teams, agency partners, media platforms, Creative, Legal, Analytics, and other required stakeholders.
Perform comprehensive pre-launch QA of campaign setup, audiences, creative, tracking, traffic allocation, test/control structures, and measurement requirements.
Monitor live experiments and proactively identify delivery issues, audience contamination, tracking concerns, platform changes, or other factors that could compromise test validity; recommend corrective action or retesting when appropriate.
Partner with Paid Media, Strategy, Analytics, agency, and business stakeholders to identify optimization opportunities and translate them into clear, testable hypotheses and experimentation plans.
Design paid media experiments using appropriate A/B, holdout, campaign-split, geo-split, or other test/control methodologies, defining audience and segmentation strategies, test cells, KPIs, sample and duration requirements, measurement approach, and success criteria based on the capabilities and limitations of each platform.
Quantify the potential financial impact of proposed paid media experiments by determining addressable audiences and media investment and estimating revenue, EBITDA, savings, or other business impact to support data-driven backlog prioritization.
Assess opportunities based on expected business impact, learning value, audience size, feasibility, scalability, and strategic importance.
Identify dependencies, risks, technical requirements, audience overlap, and potential measurement limitations during backlog grooming and prior to test activation.
Serve as the paid media experimentation subject matter expert within the broader Optimization program and partner with Strategy and Measurement leads throughout backlog grooming, sprint planning, execution, and results sharing.
Support experimentation across UOR, USH, USJ, and new ventures, adapting test designs and measurement approaches to differences in markets, audiences, media strategies, platforms, business objectives, and data availability.
Establish and maintain consistent paid media experimentation processes, documentation, measurement standards, reporting practices, and best practices.
Maintain accurate test documentation and results within program systems and learning repositories to enable transparency, historical analysis, and reuse of learnings.
Share outcomes and learnings across destinations and media teams to increase the value of experimentation and prevent duplicative testing.
Stay current on evolving paid media platform capabilities, privacy requirements, audience technologies, measurement solutions, and experimentation methodologies.
Understands and actively participates in Environmental, Health & Safety responsibilities by following established UO policy, procedures, training and team member involvement activities.
Performs other duties as assigned.