Statistical Analyst for Environmental Data

What you will do

You will work with a public-sector organisation on the statistical analysis of environmental datasets that have been collected over recent years but not yet systematically analysed. Your role combines hands‑on analysis, knowledge transfer, and team guidance.

Your work will include:

• Analysing datasets related to soil carbon monitoring, land use, surface sealing, environmental permits, and peat mapping
• Performing geostatistical analyses and working with geographical data
• Developing and applying data mining and outlier detection techniques
• Creating publication‑ready visualisations and reports using R Markdown
• Setting up and executing quality control processes for published data and documents
• Exploring Natural Language Processing (NLP) techniques for automated processing of permit decisions from unstructured PDF documents, including extraction, categorisation and interpretation of conditions and obligations
• Conducting individual analyses and guiding a team of internal staff members
• Delivering training sessions and collaborative work sessions to build internal capacity for statistical analysis
• Explaining your analyses clearly and repeating them together with colleagues so that similar analyses can be performed autonomously in the future

The organisation wants to raise the level of statistical literacy and move towards publication‑ready statistical work, with more attention to visualisation and communication of results.

What we are looking for

Essential:

• Master's or bachelor's degree with a technical or engineering background, or equivalent experience with the relevant ICT technology
• At least 10 years of experience with R
• At least 10 years of experience with statistical software packages
• At least 10 years of experience with the technology in question or similar technology
• At least 3 years of experience delivering training
• Experience in the public sector
• Dutch at CEFR level C2

Highly valued:

• Further experience within the public sector
• At least 10 years of experience with data mining and outlier detection
• Experience with data visualisation in R Markdown
• Experience with GIS analyses and geographical data
• Experience with open source development
• At least 5 years of experience with Python

Useful:

• Experience with neural networks

You are strongly communication- and analysis-oriented, with in-depth knowledge of statistical methods and their application.

The setting

This assignment runs until mid-July 2027, with a workload of around 50 per cent (approximately 768 hours in total).

You will be on‑site in Brussels one or two days per week, with the remainder of your time remote or available via Teams. A maximum of 50 per cent of the work can be done remotely.

The internal team members you will support come from diverse backgrounds, are all university‑educated, and are interested in statistical analysis.

Work is in Dutch.

You can join us for this assignment as a freelancer or as an employee of HumanInTech. Same role, same team. If you join as an employee, your employment continues beyond this assignment. When it ends, we’ll work together to find your next assignment.

Location: Brussels, hybrid

Work address: Belgium

Employer / contracting party: HumanInTech

Applications close (Brussels time): November 10, 2026 at 1:00 AM

Engagement: Freelance or employed by HumanInTech

Working hours: Full‑time

Experience: More than 10 years or more

Education: Bachelor's or more

Published: November 2026