Embedded Analytics Engineer – Healthcare AI

Rad AI; United States; Hybrid; USD 110,000 - 150,000; Full time

Benefits offered by this job

Medical, Dental, Vision & Life

HSA with employer match

401(k)

11 Paid Holidays

Flexible PTO

Annual offsite

Equipment stipend

Job summary

Rad AI is building embedded analytics inside our radiology reporting platform to give health systems self-service visibility into metrics like turnaround times and AI utilization.

The role sits at the center of data engineering, analytics, and customer engagement. You will translate ambiguous requests into rigorous, scalable metrics, working with radiology admins, IT teams, and product partners.

Qualifications

• 2–5 years in an analytics engineering, data science, or BI analytics role, with some customer-facing exposure.
• Demonstrated AI fluency with practical examples of using AI tools to describe, model, or document datasets and verify outputs.
• Strong SQL skills with complex queries and optimization.
• Working statistics fluency: confidence intervals, significance testing, sample-size considerations, handling outliers and skewed distributions.
• Experience with a modern governed BI/semantic layer tool (e.g., Omni, Looker, Sigma, ThoughtSpot) and a SQL/Python notebook environment.
• Familiarity with dbt/Snowflake-like modeling and building reusable metrics across customers.
• Ability to run discovery with external stakeholders, ask clarifying questions, and land defensible metric definitions.
• Excellent written and verbal communication to explain data findings to non-technical audiences.
• Healthcare/data-regulated domain experience is a strong plus, radiology knowledge is a bonus.

Responsibilities

• Get the data foundation right by connecting the new data platform to the warehouse and defining data contracts.
• Gather and translate requirements with radiology group admins, quality leads, and informatics teams.
• Design and build a semantic layer and reusable dashboards that scale across customers.
• Apply statistical rigor, including confidence intervals and adjustments, to healthcare reporting data.
• Use AI as a core part of the workflow to describe and document data relationships.
• Own data quality end-to-end and document caveats directly in deliverables.
• Build durable data products using dbt/Snowflake-style modeling for multi-customer reuse.
• Partner with Product, Engineering, and Customer Success to prioritize impactful metrics.
• Explain data insights to radiologists and executives in a clear, meaningful way.

Skills

SQL

AI fluency

Data modeling

Data quality

Communication

dbt

Snowflake

Python

Semantic layer

Tools

Python notebook

Looker/LookML

Job description

Rad AI is building embedded analytics inside our radiology reporting platform to give health systems self-service visibility into metrics like turnaround times and AI utilization.

The role sits at the center of data engineering, analytics, and customer engagement. You will translate ambiguous requests into rigorous, scalable metrics, working with radiology admins, IT teams, and product partners.