Data Scientist

About the role

As a Data Scientist in our Housing team, you will help turn rich, real-world housing data into trusted products and market knowledge used by both consumers and real estate professionals. Your work sits at the intersection of product, business, and market insights - using sources such as listings and sold properties to power user-facing tools and to strengthen our positioning as a market reference through data-driven insights and publications. You will act as an analytical decision partner: ensuring outputs are robust, meaningful in the real world, and translated into guidance that stakeholders can act on.

In this role you will:

Work on housing data products that create transparency and trust for users and agencies, such as:

• Valuation/estimation experiences that users can rely on (supporting the "estimation funnel")
• Prospecting and lead-support tools for realtors (e.g., fuzzy geolocalised seller lead maps)
• Leveraging sold-properties inventory so users can compare similar transactions and make informed sell/purchase decisions
• Contributing to business value levers such as conversion into listing inventory and seller lead generation

Produce market insights and content that position the brand as a market reference, including:

• Monthly/quarterly barometers and local market outlooks
• Ad hoc studies on trending topics and public policy-related questions
• Supporting press relationships and tailored market data requests, and contributing to spokesperson-ready narratives where needed

Ensure analytical excellence end-to-end:

• Validate and stress-test results; detect inconsistent or misleading outcomes; check that conclusions "make real-world sense"
• Translate analysis into actionable insights, recommendations, and guidance tools for non-technical stakeholders
• Work closely in multidisciplinary teams (economists, product managers, business, data engineers) to drive projects from idea to impact

The skills you bring:

Technical and coding skills

• Python (intermediate): pandas, numpy; data cleaning/transformation; exploratory analysis; basic visualization (matplotlib/seaborn)
• SQL (basic): data extraction; joins, filtering, aggregation
• Comfortable working with large structured datasets
• Understanding of reproducible workflows (scripts, notebooks, documentation, versioning)

Data science & analytical skills

• Statistical analysis and hypothesis testing
• Data modeling: regressions, predictive models, clustering
• Econometrics fundamentals: linear models, intuition for panel data, and bias awareness
• Strong data management and quality assessment; ability to validate and interpret results with a real-world lens

Ways of working / mindset

• Ability to communicate complex findings clearly to non-technical stakeholders
• Desire to influence decision-making through data; you operate as a partner, not just a "data provider"
• Collaborative spirit, ownership, initiative, and an action-oriented approach - following projects through from idea to analysis to impact

Languages

• Excellent English (required)
• French and/or German are a strong plus

Pay range and compensation package

Total compensation for this role: up to 65000,- EUR gross per annum.