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Marketing Data Analyst/Scientist (SEM Focus)

Ferryscanner · Athènes

New
Hybrid 🇬🇧 English
SQL BigQuery Google Analytics 4 (GA4) Looker Studio Power BI Tableau

Job description

About the role

Ferryscanner is looking for an experienced Marketing Data Analyst/Scientist to turn complex data into actionable insights that drive paid-search performance and smarter marketing investment decisions.

Key responsibilities

  • Analyse SEM and paid-search performance across campaigns, markets, products and other dimensions.
  • Partner with SEM Specialists to identify trends, inefficiencies and optimisation opportunities.
  • Extract, transform and analyse large datasets using SQL and BigQuery.
  • Combine GA4 data with advertising and business data to understand customer behaviour.
  • Build and maintain dashboards and reports that provide clear visibility into key SEM KPIs.
  • Develop forecasts and analytical models to support budget planning.
  • Investigate performance fluctuations and pinpoint drivers behind metric changes.
  • Support experimentation, performance testing and translate analysis into actionable recommendations.

Required profile

  • At least 4 years of experience as a Data Analyst, Marketing Analyst or similar role, preferably in a performance-driven, product-led, travel or consumer-tech environment.
  • Strong SQL skills with hands-on experience analysing large datasets.
  • Good understanding of SEM/PPC, paid acquisition and digital-marketing metrics.
  • Experience analysing Google Ads or other paid-search data and working with Google Analytics 4.
  • Proven ability to build dashboards and reports using Looker Studio, Power BI, Tableau or equivalent.

Required skills

  • SQL
  • BigQuery
  • Google Analytics 4 (GA4)
  • Looker Studio
  • Power BI
  • Tableau

What we offer

  • Opportunity to shape and scale Ferryscanner’s data platform and AI foundations.
  • High-impact role with direct influence on SEM performance and marketing investment.
  • Collaborative, cross-functional environment spanning Engineering, Product, Analytics and Business teams.
  • International team, continuous learning and exposure to cutting-edge data and AI technologies.
  • Hybrid working model and additional annual leave days.

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Published 1 day ago

Expires 1 month from now

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