Prada App Analytics Lead
- Seniority
- Senior
- Department
- Finance, Accounting & Revenue Management
- Industry
- Fashion, Apparel & Leather Goods
- Posted
- May 14, 2026
About %s
A Milan-based luxury fashion house operating at the intersection of creativity and commerce. Typically part of a global luxury ecosystem, the organisation combines artisanal heritage with data-driven digital transformation to optimise product, client and commercial performance across physical and digital channels.
Confidential Milan-based luxury brand seeks App Analytics Lead in Milan to lead app analytics, monetization and finance reporting.
Role & Responsibilities
- Define and own the app analytics strategy, aligning measurement with commercial and financial objectives (revenue, ARPU, LTV, retention).
- Design, implement and govern event taxonomy and instrumentation across iOS and Android (SDKs, tag plans, data layer).
- Build and maintain dashboards and automated reporting for finance, product and marketing stakeholders using enterprise BI and data-warehouse tooling.
- Translate user behaviour into actionable insights for monetization, pricing, promotions and cost-to-serve optimization.
- Lead A/B testing and experimentation programs within the app to validate product and commercial hypotheses.
- Collaborate with product, marketing, engineering and finance to prioritise analytics workstreams and translate findings into roadmap decisions.
- Manage, mentor and recruit analytics engineers / data analysts; establish best practices for data quality, lineage and documentation.
- Ensure compliance with data privacy regulations and company data governance policies in all analytics implementations.
Qualifications
- Proven leadership in digital or mobile analytics with responsibility for strategy and delivery.
- Strong technical proficiency in analytics instrumentation, event modelling and data pipelines.
- Ability to translate complex datasets into clear commercial recommendations for senior stakeholders.
- Experience working cross-functionally with product, engineering, marketing and finance teams.
- Fluent business English and the ability to communicate to non-technical audiences (language requirements not specified in source).
Skills
Experience
Minimum of 5 years in digital or app analytics, with at least 2 years in a lead or managerial capacity owning analytics strategy, instrumentation and stakeholder reporting. Proven track record in driving monetization, retention and product optimisation through data.
Education
Bachelor’s or Master’s degree in Data Science, Statistics, Economics, Finance, Computer Science or a related quantitative discipline, or equivalent professional experience.
Workplace
The successful candidate will be located in Milan, Lombardy, Italy.
Culture
The Milan-based employer blends refined craftsmanship with a progressive, data-informed approach to luxury retail. Teams operate in a fast-paced, collaborative environment that values commercial rigor, cross-disciplinary partnership and attention to detail typical of premium fashion maisons.
About %s
Cerulean is the definitive career portal for the global luxury industry. We match exceptional professionals with exclusive opportunities at the world's most prestigious brands. From haute couture and fine watchmaking to prestige beauty, hospitality, and boutique retail, Cerulean centralises luxury employment to help you find the career for which you were destined.
Frequently Asked Questions
The luxury industry is characterised by a diverse and nuanced nomenclature. Esteemed houses frequently employ proprietary terminology, and even within a single organisation like Prada, titles may vary across global markets to reflect local conventions. To ensure absolute clarity, Cerulean assigns a standardised, industry-coherent canonical title to every listing. However, it is worth noting that this role is functionally synonymous with «Mobile App Analytics Lead», «Digital Product Analytics Lead», «Head of App Analytics», «App Data Lead», and other variations. Our sophisticated search architecture anticipates these variations, ensuring that inquiries using related terms will seamlessly yield the exact roles you desire.