RealAdvisor S.A.
Data Scientist - RealAdvisor

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đź§ About RealAdvisor
RealAdvisor is one of the leading digital platforms in the European real estate ecosystem. Founded in Switzerland, we now support 7,000+ real estate agencies and attract 10+ million users per year across Europe.
We are scaling fast across multiple markets with a clear mission: help real estate professionals grow through data, transparency, and smart technology. At RealAdvisor, we value ownership, autonomy, and impact.
Role Overview
We are looking for a business-oriented Data Scientist to join RealAdvisor. You will consolidate and analyze diverse data sources (product, marketing, transactional), build ML models and experiments to drive subscription growth, and translate insights into concrete product and marketing actions. This is a hands-on, full-stack role: you will query databases, run experiments, build models, and present clear data stories to stakeholders.
Key responsibilities
- Consolidate and aggregate data from product, marketing, CRM, and transactional systems into reliable datasets.
- Perform product analytics to measure feature usage, user journeys, and retention drivers.
- Design and run experiments (A/B tests, cohort analysis, population and variation control) to validate hypotheses and measure causal impact.
- Build ML models for revenue optimization, churn prediction, segmentation, and subscription forecasting.
- Analyze marketing performance to measure acquisition efficiency, LTV, and campaign ROI.
- Translate analysis into action: propose product changes, growth experiments, and operational KPIs.
- Report results using concise dashboards, reports, and data storytelling for non-technical stakeholders.
- Work cross-functionally with product, marketing, engineering, and country managers to standardize metrics and training.
- Maintain data quality: identify polluted data, propose remediation, and implement robust ETL checks.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Required skills and experience
- 3+ years in data science, analytics.
- Python and SQL skills for data manipulation, modeling, and production prototyping.
- Experience consolidating diverse data sources and building reliable analytical pipelines.
- Experiment design and causal inference methods.
- Practical ML experience (classification, regression, segmentation) and model evaluation.
- Product analytics tools experience.
- Ability to build dashboards and present insights clearly (Looker, Tableau, Power BI, or similar).
- Business mindset: translates technical results into measurable business outcomes.
- Proactive: takes initiative, owns end-to-end delivery, and can work with limited supervision.


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Nice to have
- Experience with subscription businesses and monetization models.
- Familiarity with marketing attribution and LTV modeling.
- Frontend or backend dev experience to implement tracking or small UI changes.
- Knowledge of data engineering tools (Airflow, dbt, Spark).
- Experience working across international markets and multilingual datasets.
Why Join Us
- Fully remote.
- Full-time freelance role.
- Competitive monthly rate.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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