Analytics Engineer, Conversational Analytics

For the first 2-3 months, embed with a stakeholder team to dive into day-to-day analyst work, build stakeholder relationships, and develop business fluence

Build foundational data models, semantic models, documentation, and context that power conversational analytics across a variety of data domains (growth, product, business metrics, operations etc.)

Approach opaque, unstructured problems by developing core analytic frameworks and standardized semantic models that shape the way the company thinks about our business

Communicate and collaborate with different stakeholders to identify opportunities and build solutions that standardize our data approach to common problems across the company

Teach and guide stakeholders on best practices for using LLMs for their own data needs, and distill what works into reusable training materials

Develop and maintain AI evaluations for conversational analytics, tracking accuracy programmatically and building stakeholder feedback loops

4+ years of full-time working experience in quantitative analysis roles, with a portion of that time focused on data modeling in DBT

Hands-on experience using LLMs for coding and analytics, going beyond asking simple questions and building data products through LLM workflows

Expert-level SQL skills

Experience using BI tools (ours are Hex and Looker) to effectively convey information

Strong communication and teaching skills

Strong problem solving skills, analytical aptitude, and numerical dexterity

Demonstrated track record of project ownership