Analytics Engineer (Conversational Analytics)
Posted Updated
Description
- We are looking for an Analytics Engineer who will supercharge the organization by more fully unlocking Conversational Analytics
- You thrive in a startup setting, where every day is different and the problems that you’re tackling don’t have established solutions
- The role will have two primary focuses:
- 1) building data models/semantic models, documentation, context, and evaluations to strengthen our LLMs’ ability to consistently achieve the correct answers, and
- 2) training non-data stakeholders to more efficiently and effectively interact with our data stack
- You will start your time by diving deep into day-to-day analyst work and as you build a strong understanding for how data is used by end stakeholders and build business context
- You’ll then transition to building out tooling that allows stakeholders to self-service via Conversational Analytics
- You take pride in developing tools, processes, and working frameworks and teaching your colleagues how to use them to better leverage data to generate insights and operationalize data
- You have a bias for action, strong communication skills and a continual learning mindset
- 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
Benefits
- Medical, dental, and vision membership
- Equity for all team members
- Flexible time off
- Paid parental leave, and flexible work arrangement
- Well-stocked office with snacks and bi-weekly free lunches
- Gym, learning, and development stipends
- 4+ years of full-time working experience in quantitative analysis roles, with a portion of that time focused on data modeling in DBT
- Demonstrated track record of project ownership
- Expert-level SQL skills
- Strong problem solving skills, analytical aptitude, and numerical dexterity
- Strong communication and teaching skills
- Experience using BI tools (ours are Hex and Looker) to effectively convey information
- Hands-on experience using LLMs for coding and analytics, going beyond asking simple questions and building data products through LLM workflows
- We are open to data analysts with demonstrable interest and project experience who are looking to make the transition to analytics engineer
- Experience developing data pipelines and processes
- Experience with AI evaluation of LLM tools
