Top Data Analyst Jobs in Milan

Analyze consumer lifecycle data across acquisition, engagement, retention, and monetization to guide growth and marketing decisions. Build dashboards, reports, data models, and pipelines; contribute to data mesh and AI-powered analytics workflows. Lead experimentation and translate complex findings into actionable recommendations for Marketing, Finance, Operations, Product, and executive stakeholders.

Analyze payments data, integrate complex data sources, maintain performance reports, monitor KPIs, and identify opportunities to optimize payment routing and reduce failures and costs. The role collaborates with Payment Operations, Product, Finance, Customer Support, analysts, and engineers to ensure data quality and deliver actionable insights through ad hoc analysis, dashboards, and automated reporting.

Analyze hotel supply data to support commercial and Cloud teams, evaluate partner and chain performance, identify inventory gaps and data-quality issues, and improve reporting consistency. The role involves clarifying ambiguous requests, delivering end-to-end analyses, building trusted dashboards or data products, and communicating findings to nontechnical stakeholders. Experience with SQL is required, while dbt, data modeling, and marketplace or platform experience are advantageous.

Own analytics for Nuitee’s global travel marketplace, analyzing enterprise partners, self-service API adoption, bookings, product performance, and customer behavior. Build and validate dbt models, data pipelines, experimentation capabilities, and analytical products end to end. Partner with senior Product, Engineering, and commercial leaders to establish trusted metrics, resolve reporting inconsistencies, identify growth opportunities, and influence product and business decisions in a fast-moving startup environment.

Own product-domain KPI frameworks, analyze user behavior and product funnels, design and evaluate A/B tests, size opportunities, measure feature impact, and build self-service dashboards. Partner with Product, Design, Engineering, Operations, and executives to turn complex data into recommendations. Develop AI-assisted workflows for recurring analysis, anomaly detection, reporting, and exploration.

Owns end-to-end product and commercial analytics for an AI cloud platform, including metric definition, customer health, capacity forecasting, utilization, pricing, packaging, segmentation, and monetization. Analyzes large-scale customer and usage datasets, builds production-ready data solutions, and delivers recommendations across Product, Engineering, Finance, Sales, and Operations. The role requires strong Python, SQL, statistics, commercial judgment, and familiarity with consumption-based technical products.

Analyze large-scale user and product data, design and evaluate A/B tests, define and validate product and business metrics, build dashboards and reports, and partner with engineers, data scientists, product, and customers to translate insights into product improvements.

Analyze FMCG sales, pricing, promotions, customer, product, margin, market share, and competitor data to support revenue growth management. Develop pricing and price elasticity models, identify commercial opportunities, create visualizations and actionable insights, and translate analytical needs into product requirements, user stories, and business rules. Collaborate with stakeholders, product managers, data engineers, developers, and commercial teams to build scalable digital analytics solutions.

Lead analytical initiatives supporting Product, Data, and Business teams. Translate business and product questions into data requirements, measurement strategies, KPIs, dashboards, A/B tests, impact analyses, and actionable narratives. Track product performance, present insights to stakeholders, and coach analysts while enabling data-driven decisions across a global organization.

Analyze and improve fraud signals and user segmentation for Puzzleplay’s rewards platform. Investigate suspicious and manually reviewed users, monitor segment effectiveness, identify gaps in detection, and recommend verification tools. Collaborate with product and data teams to turn analysis into operational fraud controls across different markets as fraud patterns evolve.

Early-career Data Analyst responsible for designing and owning core metrics and dashboards, analyzing transaction/customer/credit data to inform credit, fraud, AML, portfolio and growth decisions, building data pipelines and automations with SQL and Python, partnering with cross-functional teams, and owning compliance reporting. Emphasis on turning ambiguous problems into reliable analytical systems and applying GenAI/LLMs for practical automation.

The role involves managing data transformation and reporting pipelines, automating data processes, and performing data analysis while collaborating with business owners. The candidate will use tools like Power BI and SQL in their tasks.