Top Data Analyst Jobs in Milan

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.

Work as an engineering-minded data analyst embedded in a product or CEO stream to turn raw data into trusted analytics. Build and maintain dbt models, review and refactor analytical code, define KPIs, direct AI tools to produce reports, ensure data quality, and communicate insights to stakeholders. Contribute to the data platform and its AI/semantic layer while enabling self-serve analytics for product teams and executives.

Lead finance analytics within Growth & Marketing: build P&L and cash flow reporting, investor-facing analytics, financial dashboards, unit-economics models, AI-assisted anomaly detection and automation, and design finance data models and pipelines for the company data mesh.

Analyze large datasets to identify trends and deliver actionable insights; design and monitor KPIs; build and maintain dashboards and reporting frameworks; conduct ad hoc analyses; ensure data quality and support reporting infrastructure in partnership with product and business teams.

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 Data Analyst will lead data architecture designs, develop AI workflows, create visualization tools, enhance decision-making, and collaborate with stakeholders.

Analyze and instrument offsite discovery and SEO/GEO performance for ecommerce sites. Build integrations, ETL pipelines, and models to track organic and AI-driven traffic. Create tooling and frameworks for technical site audits, landing page modelling, SEO experiments, and enablement for product and customer teams.

Lead finance analytics within Growth & Marketing: build P&L and cash‑flow models, investor reporting, dashboards, ETL/data models, unit-economics analyses, and AI-assisted workflows. Partner with Finance, Product, Marketing and senior leadership to translate financial data into actionable insights and scalable self-service assets.

Analyze and improve multilingual text data quality by developing parsers, evaluating classifiers, translating taxonomies (Skills, Titles, Occupations), cleaning data in Excel, and applying language and text-analysis expertise in collaboration with Linguistics and Engineering teams.

Analyze and improve multilingual text classifier data quality for Arabic, develop parsers with Linguistics and Engineering, translate taxonomies, clean and analyze data using Excel and related tools, and apply language and text-analysis expertise to ensure high-quality global data.

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.

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.

Lead delivery of end-to-end data and analytics solutions: build dimensional models, develop Power BI dashboards, perform exploratory analysis, design Azure-based data pipelines, capture client requirements, run scenario modelling, test and assure solutions, prepare client communications and lead project teams.

Lead data and analytics projects: design dimensional models, build Power BI dashboards, run exploratory analysis, capture client requirements, develop end-to-end data pipelines on Azure, test and assure solutions, support client decision-making, and contribute to business generation and people development.

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.

Maintain and validate global customer master data across systems (Salesforce, Jira), perform deduplication and hierarchy management, conduct compliance checks (embargo/VAT screening), monitor CMD dashboards, support cross-functional teams to resolve data anomalies, and drive data integrity projects and process 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.