Top Data Analyst Jobs in Rome

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.

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.

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.

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.

Conduct exploratory and business data analysis, build and maintain dashboards, translate stakeholder needs into data work, support experiments and investigations, and document queries and standards. Present actionable findings clearly to nontechnical colleagues while ensuring data accuracy and reliability. The role includes working with SQL and data visualization, with opportunities to use Metabase, dbt, Python, or R.

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.

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.