Lead Data Scientist

Who We Are

SmartRent (NYSE: SMRT) is revolutionizing how people live and work with the industry’s only end-to-end platform designed for the rental housing industry. By uniting purpose-built software, integrated hardware and full implementation and support in one ecosystem, we help owners and operators simplify operations, cut costs and deliver exceptional resident experiences. Recognized by Deloitte, HousingWire and the PropTech Breakthrough Awards, SmartRent is shaping the future of property technology and redefining what it means to make rental housing smarter.

Job Description

As Lead Data Scientist, you will define and execute the analytics and predictive data roadmap for SmartRent’s next-generation offerings, starting with decision-support models and machine learning for optimal property operations. You will spearhead the model development lifecycle from stakeholder collaboration to deployment within a Databricks environment.

Reporting to the SVP of Enterprise Data and AI in our new and transformational organization, you will combine quantitative rigor with practical problem-solving to deliver measurable value to internal and external stakeholders. You will partner with Data, AI, Product, and Engineering peers to solve our most complex challenges.

Responsibilities

• Frame business problems with Product and Revenue partners and turn them into modeling approaches with clear success metrics.

• Create compelling data visualizations that support insightful story telling and inform the design of predictive models.

• Build machine-learning models on large-scale time-series telemetry, including anomaly detection, failure prediction, and time-to-event models.

• Develop clean, well-documented code that promotes reuse and drives operational efficiency within the organization.

• Ship models to production on Databricks, and support their quality after launch: monitoring, diagnosing drift, and retraining.

• Partner with Engineering to scale and harden production workloads.

• Design experiments and impact analyses that tie model performance to customer and revenue outcomes.

• Set modeling standards and documentation practices for a growing team.

Required Qualifications

• Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field; or equivalent professional experience.

• 7+ years in data science, with a track record of models running in production that customers or products relied on.

• Deep expertise in time series, anomaly detection and ensemble modelling methods.

• Hands-on experience wrangling and modelling data in Databricks, plus platform capabilities like feature stores and experiment management.

• Advanced usage of SQL and Python to organize large, complex datasets.

• Strong proficiency in experiment design and causal or impact measurement.

• Passion for communicating and presenting technical concepts to non-technical audiences.

Preferred Qualifications

• Experience with applying LLMs within data science workflows, such as feature extraction from unstructured data, LLM-assisted analysis, or evaluating generative outputs.

• Experience enabling self-service data access in Databricks using features such as AI/BI Dashboards and Genie.

• Exposure to deploying machine learning pipelines end-to-end including implementing MLOps best practices.

• Experience in proptech, real estate technology, IoT, or SaaS platform environments.

• Familiarity with Git-based version control and Terraform.

We Put Our Employees First

We offer a comprehensive and competitive benefits package designed to support your well-being and future. For our US employees, this includes medical, dental, vision, and life insurance with low deductibles and 75–100% employer contributions. We also provide flexible and generous PTO (because we know how important work-life balance is), a competitive 401(k) with employer contributions, paid parental leave, discounted insurance plans for pets and legal services and an employee stock purchase plan to help you invest in your future.

You’ll fit right in if you:

• Do the hard work and go out of your way to deliver excellence

• Own outcomes and learn from your mistakes

• Are a collaborative and supportive team player—win or lose, you lift others up

• Value authenticity, diverse perspectives, and inclusion in the workplace

• Have a passion for smart tech and the real estate industry

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