Top Data Analyst Jobs in Milan

Attend local live sporting events, especially Serie A and lower-profile competitions in Italy, and record accurate real-time play-by-play data using proprietary software. The role requires strong sports knowledge, focus, reliability, and availability during evenings and weekends. Training and testing are provided, with flexible game-based work and fixed payment per game.

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.

Supports FP&A through financial planning, forecasting, scenario analysis, closing activities, dashboard development, KPI monitoring, and data-driven reporting. The role uses Excel, Power BI, SAP, and Anaplan to manage financial and operational data, identify trends and anomalies, automate processes, and deliver actionable insights to the manufacturing finance team.

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.

Build end-to-end compliance analytics and data infrastructure for KYC/KYB funnels, remediation campaigns, and financial exposure. Model and transform data with dbt and Omni, create self-service dashboards for product, ops, risk and compliance, and measure campaign impact to drive operational decisions.

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.

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.

As a Fraud Data Analyst, you will design real-time fraud strategies, develop rules to combat fraud, optimize decision-making, and collaborate with teams to enhance user experience and report performance metrics.

The Fraud Data Analyst designs real-time fraud detection strategies, optimizes decision-making tools, analyzes payment fraud, and presents data-driven insights to leadership.

Analyze and improve multilingual text classifier data quality, develop language parsers with Linguistics and Engineering teams, translate skills and occupation taxonomies, and clean data using Excel and analysis tools. The role requires Greek language proficiency, regular-expression rule writing, SQL knowledge, text analysis or machine learning familiarity, and accurate independent work.

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.

Partner with Marketing, Sales, Finance, Product and other teams to turn business questions into actionable analysis. Own end-to-end analytics: build datasets and dashboards (dbt, LookML), maintain metric definitions and caveats, use and curate agent tooling for trustworthy answers, and contribute small data platform and pipeline improvements.

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.