Data Scientist - RealAdvisor

RealAdvisor; Indiana; Hybrid; USD 78,000 - 123,000; Full time

Benefits offered by this job

Fully remote

Competitive monthly rate

Job summary

RealAdvisor is seeking a data‑driven Data Scientist to consolidate diverse data sources, build ML models, and drive subscription growth. You will run experiments, produce actionable insights, and present data stories to stakeholders across product, marketing, and country managers.

The role is fully remote, full‑time freelance, with a competitive monthly rate and cross‑functional collaboration across markets.

Qualifications

• 3+ years in data science and analytics.
• Proficient in Python and SQL for data manipulation and modeling.
• Experience building analytical pipelines and dashboards.

Responsibilities

• Consolidate data from product, marketing, CRM, and transactional systems.
• Design and run experiments to validate hypotheses and measure impact.
• Build ML models for revenue optimization and churn forecasting.
• Create dashboards and data stories for stakeholders.

Skills

Python

SQL

Experiment design

ML

Data storytelling

Business mindset

Proactive

Tools

Looker

Tableau

Power BI

Airflow

dbt

Spark

Job description

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.

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.

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.