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Salary: USD 137,300 - 166,000 / annual
Ro is building a vertically integrated healthcare platform connecting telehealth, diagnostics, pharmacy, and logistics. As an Analytics Engineer focused on Conversational Analytics, you will unlock the organization's ability to leverage LLMs for data insights and self-service analytics.
The role has two primary focuses: (1) building data models, semantic models, documentation, and evaluations to strengthen LLM accuracy for data queries, and (2) training non-data stakeholders to efficiently interact with the data stack through conversational interfaces.
You will begin by embedding with stakeholder teams for 2-3 months to understand day-to-day analyst work, build relationships, and develop business context. You'll then transition to building tooling that enables self-service conversational analytics. Your responsibilities include:
- Building foundational data models and semantic models that power conversational analytics across growth, product, business metrics, and operations domains
- Developing core analytic frameworks and standardized semantic models that shape how the company thinks about its business
- Collaborating with stakeholders to identify opportunities and standardize data approaches to common problems
- Teaching stakeholders best practices for using LLMs for data analysis and distilling learnings into reusable training materials
- Developing and maintaining AI evaluations for conversational analytics, tracking accuracy programmatically and building feedback loops
You will work on systems operating at scale with tight feedback loops and real-world impact. The team values ownership, urgency, and a bias for action, with a strong sense of purpose around patient care.
REQUIREMENTS:
- 4+ years of full-time experience in quantitative analysis roles, with a portion focused on data modeling in dbt
- Hands-on experience using LLMs for coding and analytics, building data products through LLM workflows (beyond simple queries)
- Expert-level SQL skills
- Experience with BI tools (Hex and Looker)
- Strong communication and teaching skills
- Strong problem-solving skills, analytical aptitude, and numerical dexterity
- Demonstrated track record of project ownership
Nice-to-haves:
- Experience with AI evaluation of LLM tools
- Experience developing data pipelines and processes
- Data analysts with demonstrable interest and project experience transitioning to analytics engineering are welcome to apply
