Growth Marketing Manager (Paid Analytics)
kueski · Mexico (remote) ·
- Work mode
- Remote
- Seniority
- Senior
- Category
- Marketing
- Experience
- 5+ years
kueski · Mexico (remote) ·
At Kueski, we're dedicated to improving the financial lives of people in Mexico. Since 2012, we've been the leading buy now, pay later (BNPL) and online consumer credit platform in Latin America, known for our innovative financial services. Our flagship product, Kueski Pay, provides seamless payment solutions for both online and in-store transactions, establishing itself as the preferred option for nearly 30% of Mexico's top e-commerce merchants. Notably, we were the first to introduce BNPL on Amazon Mexico.
We're a tech company with a culture geared toward innovation, collaboration, and impact, fostering a strong, diverse, and inclusive workplace. Our commitment to excellence and ethical business practices has earned us multiple industry recognitions. In 2024, we were named one of the World’s Top FinTech Companies by CNBC and recognized as one of the most ethical companies in Mexico by AMITAI. Additionally, we were certified as a Best Place to Work for LGBTQ+ Equality by HRC Equidad MX 2025 and ranked among the Best Companies for Female Talent by EFY.
Kueski is seeking a senior Growth Marketing Analytics leader to own marketing measurement end-to-end from attribution infrastructure and implementation to advanced analysis and strategic recommendations. This role requires a highly autonomous professional who can build scalable analytics frameworks, uncover second-order business impacts beyond standard attribution models, and translate complex data into actionable growth decisions.
This role is ideal for an analytical expert who thrives in high-ownership environments, enjoys connecting marketing activities to business outcomes, and can partner cross-functionally with marketing, sales, and analytics teams to optimize investment decisions and accelerate sustainable growth.
Design, implement, and continuously refine marketing attribution models across all channels, ensuring they reflect the true complexity of the customer journey.
Develop a framework to identify and account for second-order effects initiatives whose impact on brand awareness, funnel priming, or downstream conversion isn't directly attributable but is strategically significant.
Define incrementality measurement approaches (geo holdouts, intent-to-treat analyses, synthetic controls) to evaluate the true causal impact of marketing investments beyond last-touch or even multi-touch models.
Own attribution methodology decisions and communicate trade-offs clearly to stakeholders and leadership.
Lead the implementation and maintenance of tracking infrastructure: pixel setup, tag management (Google Tag Manager or equivalent), and event tracking across web and app.
Design and implement server-to-server (S2S) integrations to improve signal quality, reduce data loss from browser restrictions, and enhance campaign optimization inputs for paid media platforms.
Audit and troubleshoot data discrepancies across tracking systems, ensuring data accuracy and integrity end-to-end.
Manage and evolve the marketing analytics stack (GA4, Amplitude, third-party attribution tools, Databricks) and stay current on emerging measurement technologies and privacy-driven changes.
Partner with Data Engineering and Product to improve event schemas, tracking coverage, and data pipeline reliability.
Pull, structure, and analyze your own data independently building the analyses needed to reach conclusions and push initiatives forward, without relying on others to surface information.
Develop and maintain dashboards and reports that give clear, actionable visibility into campaign performance, channel ROI, and attribution trends.
Identify patterns and anomalies proactively; bring forward recommendations with a clear point of view, not just observations.
Use advanced analytics to correlate marketing activities with business outcomes, providing the strategic inputs needed for budget allocation and channel mix decisions.
Collaborate with Performance and Lifecycle marketing teams to translate attribution insights into concrete campaign optimizations.
Conduct A/B and multivariate experiments to validate attribution assumptions and improve measurement accuracy over time.
Help forecast marketing budgets based on attribution data and provide a clear framework for where to allocate spend for maximum ROI.
Act as the internal expert on attribution and measurement educating teams on best practices and building shared understanding across marketing, data, and finance.
5+ years of experience in marketing analytics, growth analytics, or a closely related field, with a strong track record of operating autonomously on complex, end-to-end projects.
Deep technical expertise in tracking implementation: tag management (GTM or equivalent), pixel setup, event tracking across web and mobile, and server-to-server integrations for campaign signal optimization.
Strong command of attribution modeling: multi-touch, data-driven, and incrementality-based approaches with the ability to articulate the limitations of each and when to apply them.
Developed analytical sensibility for second-order effects: able to reason about indirect, non-attributable contributions of marketing initiatives and incorporate that thinking into budget and strategy recommendations.
Proficiency in SQL and at least one BI/analytics tool (Databricks, Data Studio, Tableau, or equivalent); able to independently extract and model data without relying on data teams for every pull.
Experience with web analytics platforms (GA4, Adobe Analytics) and behavioral analytics tools (Amplitude or equivalent).
Solid understanding of digital marketing channels and their specific measurement challenges including paid social, SEM, programmatic, affiliate, and CRM.
Experience with A/B testing and statistical analysis applied to marketing measurement.
Clear, concise communicator: able to translate complex analytical findings into strategic recommendations for non-technical stakeholders and senior leadership.
Detail-oriented and proactive, with a high standard for data accuracy and a bias toward action
Experience with statistical modeling, machine learning applied to marketing (e.g., MMM, propensity models), and mentorship of junior analysts.
At Kueski we embrace diversity in all forms, systematically promote equity, and ensure everyone feels included with a sense of belonging. We are committed to the full inclusion of all qualified candidates. As part of this commitment, we will make efforts to ensure reasonable accommodations are made during the hiring process. If reasonable accommodation is needed, please let the Talent Acquisition team know.