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SmartRent is a NYSE-listed proptech platform that provides end-to-end software, hardware, and implementation services for the rental housing industry. The Data Scientist role sits within the newly formed Data and AI organization, working at the intersection of property technology and advanced analytics.
You will design, build, and deploy production-grade machine learning solutions that transform IoT telemetry, resident behavior signals, and operational data into models and decision-support tools. Key responsibilities include:
• Build supervised and unsupervised ML models (classification, regression, clustering, recommendation systems) for use cases like predictive maintenance for IoT devices, resident churn prediction, and smart access anomaly detection.
• Work within the Databricks platform to build ML workflows, manage experiment tracking, create Delta Live Tables for feature pipelines, and leverage Unity Catalog for governed data access.
• Conduct exploratory data analysis, feature engineering, and statistical hypothesis testing across structured and semi-structured data sources including device telemetry, resident events, leasing data, and support interactions.
• Develop and maintain predictive analytics solutions that inform product features and operator decision-making, such as capacity planning tools and resident experience scores.
• Monitor deployed model performance, retrain as needed, and document model drift and remediation actions to maintain production reliability.
• Collaborate with Data Engineering to integrate ML solutions into the data platform and downstream product surfaces, and partner with Software Engineering to move models from experimentation into production APIs and embedded features.
• Develop clean, well-documented, reusable code following engineering best practices and contribute to shared libraries and ML tooling.
• Translate business problems into precise analytical questions in partnership with Product and business stakeholders, and present findings to non-technical audiences including senior leadership.
• Contribute to data governance and data quality standards, respond to ad hoc analysis requests, and help build a data-driven decision-making culture.
Required: Bachelor's in Computer Science, Mathematics, Statistics, Engineering, or related quantitative field (or equivalent experience); 3+ years in data science or quantitative analytics; strong Python proficiency including production-grade codebases (PySpark a plus); proven ML model training and evaluation experience; advanced SQL skills; experience with Databricks or equivalent cloud-based lakehouse platforms; NLP techniques experience; familiarity with standard data formats; strong communication skills.
Preferred: Master's degree in quantitative discipline; hands-on Databricks ML features (MLflow, AutoML, Feature Store, Model Serving, Delta Live Tables); proptech, real estate tech, IoT, or SaaS platform experience; familiarity with IoT data patterns.
