ML Engineer / Data Scientist

About us

RE-LIVE is a next-generation real estate insights platform in its early stage focused on streamlining and modernizing the valuation process for multiple commercial and residential property types. Our mission is to enable access to property intelligence through clean UI, data integrations, and dynamic reporting, with a strong emphasis on usability and accuracy. This role will contribute directly to transforming how real estate is evaluated and reported.

Your Role

As our Machine Learning Engineer, you'll spearhead the development of predictive models for real estate pricing, incorporating a rich variety of structured and unstructured data sources. You’ll work across the full ML lifecycle—from data acquisition and preprocessing to modeling, evaluation, and front-end visualization.

Key Responsibilities

Develop and deploy machine learning models to predict real estate prices and investment potential.

Identify and transform relevant signals from heterogeneous datasets to support accurate property value predictions.

Conduct NLP-based analysis of textual data (e.g. user reviews, market reports, real estate articles) to enrich model inputs.

Collect, clean, merge, and manage large and diverse datasets from APIs, web scraping, public sources, and commercial databases.

Design and implement interactive dashboards to visualize trends, model predictions, and insights in a user-friendly manner.

Collaborate with valuation experts and product designers to integrate insights into our platform.

Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, or related field.

Strong academic background or demonstrable track record of high-impact, self-driven work in data science or machine learning.

Strong proficiency in Python and data science libraries like Pandas, Scikit-learn, NumPy.

Experience with deep learning frameworks (e.g. PyTorch, TensorFlow) for regression and NLP tasks.

Hands-on experience building interactive dashboards using Dash, Plotly, or Streamlit.

Familiarity with geospatial data and tools like GeoPandas, Shapely, or Kepler.gl is a plus.

Bonus points for knowledge of PostgreSQL / PostGIS, Elasticsearch, or LLMs for contextual insights.

What We Offer

Opportunity to build and scale a product that will redefine real estate investing in Asia and beyond.

Flexible working hours.

Collaborative, innovation-driven environment with direct access to decision-makers.

Competitive compensation and performance incentives.