About Andrea
I help marketing teams make confident, evidence-based decisions when attribution is unclear, experiments are hard to trust, and stakeholders need clear answers.
I specialize in marketing measurement and causal inference, with hands-on experience across:
- Marketing Mix Modeling (MMM)
- Geo-based experiments and lift tests
- Incrementality testing
- Causal impact analysis
I typically work with teams that:
- spend significant marketing budgets
- operate in privacy-constrained environments
- struggle to reconcile different measurement approaches
- need defensible insights to guide budget allocation
I help designing measurement approaches that work in real-world conditions and lead to actionable decisions. I take end-to-end ownership, challenge flawed assumptions when needed, and communicate clearly with both technical and senior stakeholders.
Italian
Native or bilingual
English
Fluent
French
Conversational
Remote only
Primarily works remotely
Experience
- On RunningData ScientistDecember 2024 - Today (1 year and 6 months)Zürich, Switzerland
- Driving business value via AI and advanced analytics, supporting strategic decision-making across the organization.
- Designed and executed incrementality and Geo-experiment studies that directly influence allocation of $1M+ annual media budget, demonstrating measurable ROI to senior stakeholders.
- Develop causal impact models to quantify campaign effectiveness and global event impact on sales, translating complex technical insights into actionable business recommendations for leadership.
- Built and deployed customer-level predictive models (propensity, channel affinity), covering 10M+ users and enabling CRM teams to improve ROAS by ~5% and demonstrating clear business value creation.
- Collaborate cross-functionally with marketing, product, and executive teams to align data science initiatives with business objectives and drive customer satisfaction.
- UBSData ScientistNovember 2023 - November 2024 (1 year)Zürich, Switzerland
- Delivered predictive modeling solutions for client retention that directly optimized marketing spend and decreased churn rate, working closely with business stakeholders to ensure adoption.
- Automated SQL/ETL pipelines reducing reporting time by ~30% and improving operational efficiency across teams.
- Built and presented Power BI dashboards to senior managers, driving adoption of analytics in marketing campaigns and enabling data-driven decision making at the executive level.
- AmazonBusiness Intelligence EngineerMarch 2022 - August 2022 (5 months)Luxembourg
- Created a QuickSight dashboard (similar to Tableau) adopted as the daily source of truth by the entire team, driving alignment and efficient decision-making across stakeholders.
- Tracked key business metrics (Revenues, Shipped Units, Delivery Experience) across 10+ countries, using SQL to query and manipulate ~1M rows across ~10 tables to deliver actionable insights.
- Created and automated weekly performance tracking reports for ~15 Account Managers, improving transparency, accountability, and goal achievement.
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Education
- MSc Data Science for BusinessEcole Polytechnique et HEC Paris2023MSc Data Science for Business X-HEC
- BSc Economics and Computer ScienceUniversità Bocconi2021BSc Economics, Managment and Computer Science (BEMACS)