Data Analyst Internship: Multi-Disease Anomaly Detection

Geneva Com; Paris; On-site; EUR 7,800 - 8,100; Full time

Benefits offered by this job

Stipend: 715 €/mo

Job summary

World Organisation for Animal Health (WOAH) in Paris invites a data analyst intern to build time series from official and open-source data streams for anomaly detection. You will benchmark methods across WA H I S and EIOS, develop a combined alert approach, and deliver a reproducible workflow with dashboards and automated alerts.

The role requires a master's level focus, familiarity with R/Python, SQL, Git, and dashboard tools; English communication is essential.

Qualifications

• Currently enrolled in, or recently graduated from, a master's degree (or equivalent) in Data Science, Biostatistics, Statistics, Applied Mathematics, or Epidemiology with a strong quantitative component.
• No professional experience required, but relevant experience through coursework, an academic project or a previous internship is expected.
• Basic knowledge of time series analysis; experience writing reproducible analytical code; basic dashboard development experience; understanding of how detection and surveillance systems are evaluated (sensitivity, PPV, timeliness).
• Technical skills: R and/or Python, SQL, Git, reproducible reporting (Quarto/R Markdown), dashboards (Shiny, Dash, Power BI). Good communication skills in English; other WOAH languages appreciated.

Responsibilities

• Build time series from WAHIS and EIOS suitable for anomaly detection by disease, country/territory and region.
• Benchmark anomaly detection algorithms across both streams and evaluate their ability to warn of the start of an epidemic wave, the approach of its peak and its post-peak decline.
• Compare EIOS and WAHIS anomalies and propose a combined alert rule.
• Consolidate the work into a reproducible, version-controlled and documented pipeline that WOAH staff can run, maintain, update and host, with automated data updates, quality checks and analytical reports (e.g. Quarto).
• Design and develop dashboards and automated alerts presenting early warning outputs.
• Produce methods documents, a user guide, a final report and a presentation of results to WOAH staff.

Skills

R

Python

SQL

Git

Quarto

Shiny

Dash

Power BI

Time series

Dashboard

English communication

Education

Master's degree in Data Science or related fields

Tools

R

Python

SQL

Git

Power BI

Shiny

Dash

Quarto

Job description

World Organisation for Animal Health (WOAH) in Paris invites a data analyst intern to build time series from official and open-source data streams for anomaly detection. You will benchmark methods across WA H I S and EIOS, develop a combined alert approach, and deliver a reproducible workflow with dashboards and automated alerts.

The role requires a master's level focus, familiarity with R/Python, SQL, Git, and dashboard tools; English communication is essential.