Who we are
Luxembourg National Data Service (LNDS) is a brand of PNED G.I.E. an organisation created by the Luxembourg Government, to implement Luxembourg’s strategies in research, innovation, and digitalisation. LNDS enables value creation from secondary use of data, for public and private partners and supports the sharing and re-use of public sector data, in a trustable manner. The LNDS service portfolio includes know-how, capabilities, tools, infrastructure, and data services. Through efficient & responsible use of data and improving the secondary use of data, LNDS will support the acceleration of economic, ecological, and societal transitions.
www.lnds.lu | LNDS on LinkedIn
Purpose of the job / project
At LNDS, we aim to enable the responsible and impactful use of data to support research, innovation, and public policy.
We are looking for a Senior Data Scientist to contribute to the MMUST+ project (Multimodal Model
and Cross-Border Mobility Scenarios), a European initiative focused on modelling mobility systems
and assessing the impact of public policies across the Greater Region.
In this role, you will develop and apply advanced modelling and analytical methods to simulate
mobility patterns, explore future scenarios, and generate insights to support evidence-based decisionmaking.
You will work at the intersection of data science, modelling, and public policy, in collaboration with
international research partners and multidisciplinary teams.
What you will do
As a Senior Data Scientist, your main role will be to:
- Design and implement advanced modelling approaches to analyse mobility systems and policy scenarios
- Contribute to the development and evolution of simulation models within the MMUST+ framework
- Translate complex analytical results into clear, scientifically robust, and policy-relevant insights
- Collaborate closely with research institutions and project partners in a multi-country consortium
- Contribute to other LNDS projects and data initiatives by bringing expertise in the mobility domain as well as modelling expertise and analytical methodologies
- Analyse and interpret complex datasets related to mobility, population, and behavioural patterns
- Develop and implement quantitative models (e.g. simulation, econometric, or behavioural models)
- Contribute to the design and implementation of scenario-based analyses (e.g. forecasting, backcasting)
- Ensure the scientific quality, robustness, and reproducibility of modelling outputs
- Produce technical reports, scientific contributions, and presentations for project stakeholders
- Participate actively in the MMUST+ consortium, including technical discussions and deliverables
- Work with multidisciplinary teams (data scientists, researchers, policy experts)
- Contribute to the planning and execution of project tasks and milestones
- Represent LNDS in selected project meetings and technical exchanges
- Act as a reference expert within LNDS, delivering structured knowledge transfer (workshops, documentation, methods) to enable colleagues to understand, reuse, or contribute to MMUST+ modelling approaches
- Proactively support capability building, by facilitating onboarding of selected LNDS team members into relevant methodologies, tools, or datasets linked to the project
- Where relevant, support other LNDS data projects by providing knowledge from the mobility domain and modelling expertise or analytical input
Who you are
Required
- MSc or PhD in a data-intensive or quantitative field (e.g. transportation, economics, engineering, geography, data science, or related fields)
- Strong experience in advanced data analysis and modelling, including: statistical modelling, econometrics, or simulation approaches
- Experience in the full data analysis lifecycle (problem definition → methodology → analysis → communication)
- Proficiency in at least one scientific programming language (e.g. Python or R)
- Experience working in collaborative research or multi-partner projects (e.g. EU-funded initiatives)
- Strong scientific writing and communication skills
- Excellent command of English
Optional (considered as advantages)
- Experience in transport modelling, mobility analysis, or spatial data analysis
- Familiarity with agent-based modelling or simulation frameworks
- Experience working at the interface between data analysis and public policy
- Experience presenting results in international or multidisciplinary environments
- You have a working knowledge of one of Luxembourg’s official languages (French, German, or Luxembourgish).
