Measurement Partner for Performance CoE- Brazil

onal teams such as sales, product marketing, measurement product and business marketing to ensure that clients and agencies have best-in-class support.

The role within the CoE is a hands-on, highly collaborative role that blends strategy, statistical rigor, and enablement. You will co-own global learning agendas, design and operationalize experimentation at scale, and develop playbooks and frameworks (e.g., causal experiments, ad-stock & saturation, cross-channel attribution hygiene) that raise the bar for how our regions plan, test, and optimize. You will also coach practitioners, review code and methods, and turn proof-of-concepts into repeatable programs.

Responsibilities
Global strategy & governance

• Co-design global learning agendas and experimentation roadmaps with Sales, Product Marketing, and regional Marketing Science teams.
• Establish standards for design, analysis, documentation, and decisioning (e.g., hypothesis templates, guardrails, code review, reproducibility).
• Translate complex methods into clear recommendations for executives and practitioners.
  Experimentation & causal inference at scale
• Architect and QA A/B, geo-lift, incrementality, and calibration studies; select appropriate designs under privacy and data constraints.
• Build scalable templates that regional teams can reuse with minimal modification.
• Run post-test evidence reviews to codify learnings and update learnings.
  Performance science frameworks
• Develop and maintain approaches for ad-stock/decay, saturation & elasticity, budget-reallocation simulators, and incremental ROAS estimation.
• Diagnose interactions across levers (e.g., brand → performance spillovers) and communicate trade-offs in plain language.
  Code, methods, and enablement
• Conduct method and code reviews (statistical assumptions, diagnostics, data QA, reproducibility).
• Create and deliver training (live sessions, office hours, self-serve modules) on different statistical concepts.
• Write reference implementations and concise documentation that others can maintain.
  Cross-functional influence
• Partner with Product/Measurement Product to provide field feedback and shape roadmaps; pilot new features with lighthouse clients.
• Work with regional leaders to adapt global frameworks to local market structures and constraints; scale PoCs into programs.
  Client & stakeholder impact
• Join senior client conversations as a trusted advisor, guiding how to test, measure, and act.
• Convert insights into clear actions (budget moves, creative/media levers, sequencing) and measure the business impact of those actions.
• Manage client and agency feedback to ensure their voice is reflected with our product and partnerships teams

Qualifications

Minimum Qualifications

• At least 3-5 years of experience with digital advertising, large marketing-related organizations, or measurement suppliers.
• Expertise in advertising data, measurement methods and statistical model; Demonstrated expertise in measurement design (A/B, geo/market tests, lift studies, calibration) and statistical modeling (ad-stock/decay, saturation, elasticity).
• Basic knowledge in R or Python and SQL; comfort reviewing code and enforcing reproducibility standards (versioning, environments, documentation).
• Successful examples where past measurement contributions led to behavior change and experience influencing senior stakeholders.
• A track record of inferential problem solving through experimental design and analytical methods
• Proficient in English (written and verbal) across technical and non-technical audiences due to supporting Global teams/clients
• Strong prioritization and program-building mindset: start with PoC, scale to playbook.

Preferred Qualifications

• Relevant bachelor's degree in Business, Advertising, Economics, Computer Science, Statistics or Research.
• Familiarity with privacy-first innovation for measurement systems is a plus
• Experience working with sales and cross-functional teams
• Experience with advertising agencies or advanced marketing data-driven organizations preferred
• Familiarity with MMM/advanced attribution (as inputs to experimentation, not as a replacement)
• Experience working across multiple regions/time zones and with agencies or large advertisers.