Network Insights Analyst

Ookla; España; Presencial; EUR 60.000 - 67.000; Jornada completa

Descripción de la vacante

Ookla is seeking a Network Data Analyst to translate large-scale telecom data into actionable insights for customers and internal teams. The role focuses on analytical methods for pre-sales and post-sales adoption, with experience in crowdsourced data as a strong plus.

You will analyze network performance metrics, develop data stories and visualizations, and collaborate with Sales, Customer Solutions, and Data Engineering to ensure data quality and impact.

Formación

• 3+ years of data science, analytics, or BI in telecom or connectivity domains.
• Strong SQL skills and experience querying large-scale datasets.
• Experience using Python or R for data analysis and modeling.
• Foundational understanding of mobile or broadband network performance metrics.
• Experience with crowdsourced or large-scale observational datasets preferred.
• Ability to communicate insights to technical and non-technical audiences.

Responsabilidades

• Analyze large-scale telecommunications and network performance datasets, including crowdsourced data.
• Provide customer-specific analysis, benchmarks and data-driven insights for pre-sales.
• Develop clear insights, visualizations and data stories for stakeholders.
• Collaborate with Sales, Sales Engineering and Customer Solutions during deal qualification.
• Support post-sale analysis and validation for adoption and outcomes.
• Ensure data quality and usability with Data Engineering and Product teams.

Conocimientos

SQL proficiency

Data analysis

Communication

Herramientas

Python

R

SQL databases

Descripción del empleo

Ookla is seeking a Network Data Analyst to translate large-scale telecom data into actionable insights for customers and internal teams. The role focuses on analytical methods for pre-sales and post-sales adoption, with experience in crowdsourced data as a strong plus.

You will analyze network performance metrics, develop data stories and visualizations, and collaborate with Sales, Customer Solutions, and Data Engineering to ensure data quality and impact.