Analytics & Insights Specialist

We are looking for a Analytics & Insights Specialist with strong technical expertise and strategic vision to lead the generation of actionable insights that drive commercial and digital marketing decisions. This role will be responsible for transforming large volumes of data into clear, compelling stories, predictive models, and recommendations that deliver measurable business impact. The successful candidate will work cross-functionally with Marketing, Product, Commercial, and Technology teams in a dynamic, innovation-driven regional environment. Role Mission Turn data from our digital ecosystems into a competitive advantage by combining advanced analytics, machine learning, and a deep understanding of digital marketing — answering strategic business questions, uncovering growth opportunities, and effectively communicating findings to both technical and executive audiences. Key Responsibilities Analytics & Insight Generation Design and execute advanced analyses on user digital behavior, campaign performance, and conversion funnels to identify patterns, opportunities, and risks. Generate actionable insights that answer strategic business questions and translate into concrete recommendations for Marketing, Product, and Commercial teams. Build data storytelling narratives that connect analytical findings to business decisions, tailoring the message to technical, managerial, and executive audiences. Define KPIs, measurement frameworks, and attribution models that holistically evaluate the performance of the digital ecosystem. Data Architecture & Analytics Engineering Build and maintain robust data pipelines in BigQuery from sources such as GA4, CRM, media platforms, and transactional databases. Design efficient, optimized SQL queries on large-scale tables, including Google Analytics 4 export tables (events_*). Collaborate with Data Engineering teams on data modeling, quality, governance, and availability across GCP and AWS environments. Visualization & Communication of Results Design and maintain executive dashboards in Looker Studio (or other BI tools) that deliver clear, timely, and actionable information to stakeholders. Present findings to C-level audiences, translating complex technical analyses into simple, actionable, business-oriented messages. Document methodologies, assumptions, and analytical limitations to ensure transparency and reproducibility. Collaboration & Technical Leadership Act as a technical reference within the Analytics & Insights team, supporting junior analysts on best practices in SQL, Python, and modeling. Collaborate with regional teams across multiple markets, understanding local nuances and consolidating learnings at a regional level. Promote a data-driven culture, advocating for the responsible use of data and experimentation as a driver of decision-making. Requirements Education Bachelor's or Master's degree in Statistics, Data Science, Engineering, Economics, Mathematics, Industrial Engineering, or related fields. Relevant certifications are a plus: Google Analytics, Google Cloud (Data Engineer / Data Analyst), AWS (Data Analytics), or equivalents. Experience Experience in advanced analytics, data science, or business intelligence roles, preferably in digital, telecommunications, e-commerce, or media industries. Demonstrated experience leading end-to-end analytics projects: from problem definition to implementation and communication of results. Experience in regional or multinational environments is a strong plus. Required Technical Skills Google Analytics 4 (GA4): configuration, implementation, advanced analysis, and BigQuery export (events_*, intraday tables, event parameters, attribution). BigQuery / Advanced SQL: designing efficient queries, window functions, partitioning, cost optimization, and integration with GA4 and transactional data. AWS: hands-on experience with data services such as S3, Athena, Glue, Redshift, or equivalents. Python: data manipulation (pandas, numpy), visualization (matplotlib, seaborn, plotly), and modeling (scikit-learn, statsmodels). Machine Learning: command of supervised and unsupervised algorithms (regression, classification, clustering), model validation, performance metrics, and experimentation. Digital Marketing: deep understanding of the digital ecosystem (paid media, SEO, CRM, CRO, attribution, conversion funnels, customer journey). Data Visualization: Looker Studio, Power BI, Tableau, or similar tools. Nice-to-Have Skills Experience with dbt, Airflow, or other orchestration and analytics modeling tools. Knowledge of experimentation platforms, CRO tools (Microsoft Clarity, Hotjar, Optimizely), and behavior analytics. Familiarity with causal inference frameworks (CausalImpact, DiD, propensity scoring). Experience with generative AI tools applied to analytics and productivity. Core Competencies Analytical & critical thinking: ability to break down complex problems and draw rigorous conclusions from data. Insight generation: ability to go b