About the job
About Rebar
Rebar is revolutionizing the commercial HVAC, Electrical, and Plumbing supply industry by developing a cutting-edge operating system. Our AI-driven quoting engine is expanding across leading suppliers in North America, making measurement and evaluation crucial to our infrastructure.
As a Data Analytics Engineer, your mission will be to construct systems that provide insights into our AI's performance in real-world scenarios—analyzing successes and failures, and assessing their influence on business outcomes. You will establish essential product metrics, create monitoring frameworks, and deliver both internal and customer-facing data products that convert raw model outputs into reliable intelligence.
This role sits at the crossroads of AI evaluation, product analytics, and data-driven product development. You will not only develop innovative data products that enhance customer value but also track the real-world performance dynamics of our AI systems, informing internal teams and stakeholders for better decision-making. If you are passionate about building analytic infrastructures and measurement systems as well as addressing significant business questions, this position is tailored for you.
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.
Proficient in Python, skilled in SQL, and experienced with Data Warehousing.
Demonstrated experience handling large, real-world datasets and navigating ambiguous problem definitions.
Proficient in writing modular, testable analytics code and familiar with version control environments.
Ability to design meaningful metrics and evaluation frameworks for complex systems from the ground up.
Experience in building data visualizations and dashboards.
1–3 years of experience in analytics engineering, data science, or product analytics roles working with production data systems.
Excellent communication skills for conveying quantitative insights to both technical and non-technical audiences.
Responsibilities
Design and develop data-driven product features utilizing Rebar’s historical datasets.
Define, implement, and productionize metrics to monitor AI system performance over time, including automated tracking and monitoring of regressions and drift.
Analyze model failure modes across documents, projects, customers, and time, communicating findings effectively...

