top of page

Head of Data Engineering

About Livano

At Livano, we are redefining how property decisions are made. We believe that in an increasingly complex real estate market, data shouldn't just be "available"—it should be intelligent. By combining advanced Machine Learning with massive-scale data ingestion, Livano provides instant, high-confidence property valuations and market insights. We are looking for a visionary Head of Data Engineering to build the backbone of our intelligence platform.

​

The Role

As the Head of Data Engineering, you will own the end-to-end data lifecycle that powers our AI. You aren't just managing a team; you are architecting a "data factory" that ingests millions of points from public records, MLS, geospatial sensors, and alternative data sources. You will lead the transition from raw data to the "knowledge assets" that fuel our Automated Valuation Models (AVMs).

​

Key Responsibilities

  • Strategy & Vision: Define the technical roadmap for Livano’s data platform, ensuring it scales to handle 10x growth in data volume and complexity.

  • Team Leadership: Recruit, mentor, and lead a high-performing team of Data and Analytics Engineers. You will foster a culture of "Data Beats Opinions."

  • Data Architecture: Design and oversee a modern, modular data stack (e.g., Snowflake, Databricks, dbt) that supports both batch and real-time streaming (Kafka/Kinesis).

  • AVM Enablement: Partner closely with Data Science to build the feature stores and pipelines necessary for high-accuracy property prediction models.

  • Data Governance & Quality: Implement rigorous data observability and quality frameworks to ensure our AVMs are never "hallucinating" due to bad input data.

  • PropTech Integration: Manage complex integrations with 3rd-party data providers, MLS feeds (RESO API), and geospatial datasets.

​

What We’re Looking For

  • Experience: 10+ years in Data Engineering, with at least 3-5 years in a leadership role (Head of or Director level) within a high-growth tech environment.

  • The Stack: Expert-level knowledge of Python, SQL, and cloud infrastructure (AWS/GCP). Deep experience with dbt, Airflow/Dagster, and Snowflake or BigQuery.

  • Domain Expertise: Prior experience in PropTech (similar to: Zillow, Zoopla, Rightmove) or FinTech is highly preferred. You understand the "messiness" of real estate data.

  • Mindset: You are "hands-on enough" to dive into a PR when needed, but strategic enough to present the data roadmap to the Board.

  • Education: BS/MS in Computer Science, Engineering, or a related quantitative field.

​

Why Livano?

  • Impact: Your work directly dictates the accuracy of our flagship AI products.

  • Innovation: We don't have "legacy debt." You get to build the dream stack from the ground up.

  • Equity: Competitive salary plus a significant equity stake in a fast-growing PropTech leader

 

Data Science Lead

About Livano

At Livano, we are redefining how property decisions are made. We believe that in an increasingly complex real estate market, data shouldn't just be "available"—it should be intelligent. By combining advanced Machine Learning with massive-scale data ingestion, Livano provides instant, high-confidence property valuations and market insights. We are looking for a visionary Data Science Lead to enhance our predictive & AI models.

​

The Role

As the Data Science Lead at Livano, you will be the primary architect of our proprietary intelligence engines. You will lead the development, deployment, and optimization of our Automated Valuation Models (AVMs) and predictive analytics tools. This is a "player-coach" role where you will set the scientific standard for the team, translate business goals into mathematical problems, and ensure our AI provides the most accurate property insights in the market.

​

Your Mission

To move Livano beyond simple "comparable sales" and into the realm of Deep Property Intelligence. You will lead a team in uncovering the hidden correlations between geospatial data, economic trends, and property characteristics to predict the future of real estate.

​

Key Responsibilities

  • AVM Leadership: Own the lifecycle of our core valuation models, from feature engineering and hyperparameter tuning to A/B testing and production deployment.

  • Feature Innovation: Explore unconventional data sources—satellite imagery, school district sentiment, transit expansion plans, to find new signals that drive property value.

  • Strategic Roadmap: Work with the Product and Engineering teams to define which AI capabilities (e.g., image recognition for home condition, rental yield forecasting) we build next.

  • Mentorship: Lead and grow a team of Data Scientists and ML Engineers, fostering a culture of rigorous experimentation and "fail-fast" research.

  • Explainable AI (XAI): Develop methods to make our AI "interpretable" so that users understand why a property is valued at a certain price.

  • Quality Benchmarking: Define and track model performance metrics (MAE, MAPE, PPE10) against industry standards to ensure Livano remains a market leader.

​

What We’re Looking For

  • Education: PhD or Masters in a quantitative field (Statistics, Physics, Computer Science, Economics, or similar).

  • Experience: 7+ years in Data Science, with at least 2 years leading teams in a production environment (PropTech or FinTech preferred).

  • Technical Mastery: * Expert-level Python and libraries (XGBoost, LightGBM, PyTorch/TensorFlow).

  • Deep understanding of Geospatial Analysis (GIS, PostGIS, Geopandas).

  • Experience with Cloud ML platforms (SageMaker, Vertex AI, or Databricks).

  • The "PropTech" Edge: Knowledge of real estate market dynamics and the unique challenges of "thin" or "noisy" property data.

  • Communication: The ability to explain a "Gradient Boosted Tree" to a real estate agent or a Board member with equal clarity.

 
Why Livano?

  • Pure Ownership: You aren't a cog in a machine; you are the driver of our core product.

  • Data Richness: Access to massive, diverse datasets that allow for true creative experimentation.

  • Modern Stack: We believe in using the best tools available, from dbt to Snowflake to Weights & Biases.

 

bottom of page