数据科学家 - RealAdvisor
Data Scientist - RealAdvisor
🧭 关于 RealAdvisor
RealAdvisor 是欧洲房地产生态系统中领先的数字平台之一。我们成立于瑞士，目前支持 7000+ 家房地产公司，并每年在欧洲吸引超过 1000 万用户。
我们正在多个市场快速扩展，使命明确：通过数据、透明度和智能技术帮助房地产专业人士成长。在 RealAdvisor，我们重视主人翁精神、自主权和影响力。
职位概述
我们正在寻找一位以业务为导向的数据科学家加入 RealAdvisor。你将整合和分析多种数据源（产品、营销、交易），构建机器学习模型和实验以推动订阅增长，并将洞察转化为具体的产品和营销行动。这是一个动手能力强、全栈式的工作：你将查询数据库、运行实验、构建模型，并向利益相关者展示清晰的数据故事。
职责要点
- 从产品、营销、CRM 和交易系统中整合和聚合数据，形成可靠的数据库。
- 进行产品分析，衡量功能使用情况、用户旅程和留存驱动因素。
- 设计并运行实验（A/B 测试、群体分析、对照组和实验组控制）以验证假设并测量因果影响。
- 构建用于收入优化、流失预测、细分和订阅预测的机器学习模型。
- 分析营销表现，衡量获客效率、客户终身价值（LTV）和广告活动投资回报率（ROI）。
- 将分析结果转化为行动：提出产品改进、增长实验和运营关键绩效指标（KPI）。
- 使用简洁的仪表盘、报告和数据叙事向非技术人员汇报结果。
- 跨职能与产品、营销、工程和国家经理合作，统一指标和培训。
- 维护数据质量：识别数据污染，提出修复方案，并实施稳健的 ETL 检查。
所需技能和经验
- 3 年以上数据科学或分析经验。
- 熟练使用 Python 和 SQL 进行数据处理、建模和生产原型开发。
- 具备整合多种数据源并构建可靠分析流程的经验。
- 实验设计和因果推断方法的经验。
- 实践机器学习经验（分类、回归、细分）及模型评估能力。
- 使用产品分析工具的经验。
- 能够构建仪表盘并清晰地呈现洞察（如 Looker、Tableau、Power BI 或类似工具）。
- 商业思维：能将技术结果转化为业务价值
查看英文原文
🧭 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.
Requirements
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.
Benefits
Why Join Us
- Fully remote.
- Full-time freelance role.
- Competitive monthly rate.
Originally posted on Himalayas