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 geo-localised 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 modelling: 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 → analysis → 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.