Top Data Analyst Jobs in Italy

Leads ad hoc and exploratory analyses for medical and business questions across a global Medical Insights organization. Prepares and validates datasets, translates ambiguous stakeholder needs into decision-ready findings, and maintains analytical documentation. Tests new data sources, methods, and AI-enabled approaches through proof-of-concept analyses to guide platform investments and roadmap decisions. Partners with business and product stakeholders while supporting compliant, reproducible use of regulated data.

Intern will support updating and maintaining the GTS Aero Qualification database, create standard templates and dashboards, improve processes and data-driven tools, monitor repair qualification program performance, learn internal software, collaborate with cross-functional teams, and apply HS&E standards.

Collects, manages, and analyzes online payment data to identify trends, monitor volumes, costs, platform performance, and KPIs. Creates Power BI or Looker reports and ad hoc analyses for leadership, recommends data-driven improvements, and collaborates with product, IT, Finance, fraud, customer care, and Legal teams to improve payment operations.

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.

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.

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.

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.

Support consolidation of operational data across sites, maintain Excel-based reports and dashboards, monitor KPIs, prepare performance review materials and presentations, assist supplier coordination and action-tracking, and contribute to continuous improvement while collaborating with operations, supply chain, and procurement teams.

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.

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.

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

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.

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.

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.