Lead Data Scientist

SmartRent; Dallas (TX); On-site; USD 130,000 - 180,000; Full time

Benefits offered by this job

Health insurance

Paid time off

401(k) with employer contributions

Parental leave

Employee stock purchase plan

Job summary

SmartRent seeks an experienced Senior Data Scientist to define and execute analytics roadmaps in an onsite Dallas role. You will lead end-to-end model development from framing problems to deploying in Databricks, driving measurable outcomes for customers and the business.

You will collaborate with stakeholders, build predictive models (time-series, anomaly detection, ensembles), and translate insights into actions. Strong SQL/Python and production experience are required.

Qualifications

• Bachelor’s degree in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field, or equivalent professional experience.
• 7+ years of data science experience, including models in production that customers rely on.
• Deep expertise in time series, anomaly detection, and ensemble modeling.
• Hands-on Databricks experience, including feature stores and experiment management.
• Advanced SQL and Python for large, complex datasets.
• Strong ability to design experiments and measure causal or impact effects.
• Ability to communicate technical concepts to non-technical audiences.

Responsibilities

• Collaborate with Product and Revenue to frame business problems and define success metrics.
• Build data visuals to communicate insights and guide model development.
• Develop machine-learning models using large-scale time-series telemetry, including anomaly detection and time-to-event modeling.
• Write clean, well-documented code for reuse and efficiency.
• Deploy models to production in Databricks and monitor performance, drift, and retraining.
• Partner with Engineering to scale production workloads.
• Design experiments and impact analyses linking model performance to outcomes.
• Set modeling standards and documentation practices for the data science team.

Skills

Time series

Anomaly detection

Ensemble modeling

SQL

Python

Experiment design

Communication

Education

Bachelor’s degree in Computer Science/Math/Statistics/Engineering

Tools

Databricks

Git

Terraform

Feature stores

Job description

SmartRent is building next-generation offerings that improve property operations through analytics and predictive machine learning. In this onsite role in Dallas, TX, you will define and execute the analytics roadmap, starting with decision-support models and extending into production deployments that drive measurable outcomes for customers and the business.

You will lead model development from problem framing through Databricks deployment, working closely with stakeholders to ensure the models perform reliably in real-world conditions and translate into tangible impact.

What you’ll do

• Collaborate with Product and Revenue partners to frame business problems, define success metrics, and translate them into modeling approaches.
• Build data visualizations that communicate insights and inform the direction of predictive model development.
• Develop machine-learning models using large-scale time-series telemetry, including anomaly detection, failure prediction, and time-to-event modeling.
• Write clean, well-documented code designed for reuse and operational efficiency across the organization.
• Deploy models to production within a Databricks environment, then support ongoing quality through monitoring, drift diagnosis, and retraining.
• Partner with Engineering to scale and harden production workloads.
• Design experiments and impact analyses that connect model performance to customer and revenue outcomes.
• Set modeling standards and documentation practices for a growing data science team.

Requirements

• Bachelor’s degree in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field, or equivalent professional experience.
• 7+ years of data science experience, including a track record of models running in production that customers or products relied on.
• Deep expertise in time series, anomaly detection, and ensemble modeling methods.
• Hands-on experience wrangling and modeling data in Databricks, including platform capabilities such as feature stores and experiment management.
• Advanced proficiency in SQL and Python for organizing large, complex datasets.
• Strong skills in experiment design and causal or impact measurement.
• Ability to communicate and present technical concepts to non-technical audiences.

Technologies

• Databricks, SQL, Python
• Feature stores, experiment management, MLOps
• LLMs, AI/BI Dashboards, Genie
• Git-based version control, Terraform

Preferred qualifications

• Experience applying LLMs within data science workflows (for example, feature extraction from unstructured data, LLM-assisted analysis, or evaluating generative outputs).
• Experience enabling self-service data access in Databricks using capabilities such as AI/BI Dashboards and Genie.
• Exposure to deploying end-to-end machine learning pipelines with MLOps best practices.
• Experience in proptech, real estate technology, IoT, or SaaS platform environments.
• Familiarity with Git-based version control and Terraform.

Benefits

• Medical, dental, vision, and life insurance with low deductibles and 75–100% employer contributions
• Flexible and generous PTO
• Competitive 401(k) with employer contributions
• Paid parental leave
• Discounted insurance plans for pets and legal services
• Employee stock purchase plan