Top Data Analyst Jobs in Italy

Analyze lease and rent data to identify savings opportunities and support procurement decisions. Maintain accurate lease information across real estate systems, validate portfolio data with international teams, track global rent-saving initiatives, and coordinate external suppliers and stakeholders. The six-month Milan internship requires advanced Excel skills, familiarity with Power BI or Tableau, strong English, and an interest in data analysis and indirect procurement.

Own marketing attribution models and incrementality testing across Google Ads and Meta Ads. Design geo tests and conversion lift studies, explain performance changes to stakeholders, build the testing roadmap, and align Growth and Finance on evidence-based budget decisions. Use SQL, BI tools, and AI throughout the analytics workflow.

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.

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 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.

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 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.

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 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.

Develop analytical and machine learning solutions for consulting clients across industries. Responsibilities include designing solutions, building prototypes, evaluating model effectiveness, explaining data science concepts to clients, and collaborating with colleagues globally. Projects involve NLP, credit risk modeling, portfolio decarbonization, promotion analytics, GenAI validation, supply chain risk, and customer churn modeling.

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.

Supports consulting clients by designing analytical solutions, developing machine learning and statistical models, building prototypes, validating AI tools, and communicating complex data science concepts. Projects span financial services, risk management, sustainability, retail, supply chain, and customer analytics. The role involves close collaboration with colleagues and clients, continuous technical learning, and occasional international travel.

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.

Support the Aeroderivative Engines team by maintaining databases, creating reports and dashboards, analyzing large datasets into KPIs, improving data-driven tools and processes, and presenting insights to project managers while applying HS&E standards.

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.

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.

Design, build and maintain interactive BI dashboards, perform exploratory analysis on commodity markets, ensure data quality and pipelines, produce KPIs and insight reports, and support stakeholders with self-service analytics and training.

Work on client-facing data science and analytics projects: design analytical solutions, build and validate ML/NLP/GenAI prototypes, implement models and toolkits, communicate insights to clients, and support cross-industry engagements (financial services, energy, retail, telecom). Collaborate in teams, travel internationally, and contribute to project delivery and client impact.

Collaborate with clients to design and implement data-driven solutions, build ML/NLP/GenAI prototypes, develop credit risk and probability-of-default models, analyze datasets, validate analytical approaches, and communicate results to stakeholders while working across teams.

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.