Data Scientist, Internet Researcher Job Description

Title: Data Scientist, Internet Researcher 

Duration: 9-12 months

Hours per week: Part-time

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Job description: This role focuses on analyzing large-scale Internet measurement data to generate actionable insights that support evidence-based policy making for connectivity in schools. You will design and apply analytical and research methodologies, combine diverse datasets, and translate complex findings into clear insights, visualizations, and reports. This work will directly inform international efforts to identify bottlenecks in connectivity, improve monitoring, and strengthen research in Internet measurement in partnership with UNICEF Giga.

Duties & Responsibilities 

  • Conduct deep-dive analyses of measurement datasets (speed tests, traceroutes, etc.) to identify patterns, discrepancies, and reliability issues.

  • Combine various Internet measurement datasets to obtain insights

  • Generate actionable insights to support monitoring and policy-making which include schools and government agencies (e.g. education, telecommunications). 

  • Collaborate with partner organizations (e.g. Giga, ISOC Pulse) on joint research and analysis efforts.

  • Build proof-of-concepts (PoCs) for data visualization and reporting. 

  • Contribute to research on Internet measurement and data-driven connectivity monitoring.

Required Skills and Qualifications:

  • Experience working with Internet measurement data, including speed test results and traceroutes. 

  • Familiarity with Internet measurement protocols and datasets (e.g. TCP/IP, BGP).

  • Strong proficiency in Python (including, Jupyter/Colab, data science and visualization libraries).

  • Proficiency with SQL and Google BigQuery.

  • Experience with Git-based workflows and CI/CD pipelines.

  • Solid background in data analysis, visualization, and reporting.

  • Strong organizational and written/verbal communication skills.

Preferred Qualifications 

  • Experience contributing to or maintaining open-source software projects.

  • Experience with statistical analysis and or machine learning techniques

  • Familiarity with M-Lab tools and datasets (e.g., NDT, Traceroute)

  • Research experience with a track record of publications or technical reports.

  • Experience with containerized/cloud-native environments (Docker, Kubernetes, Linux, Bash).

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