Analytics Engineer, Conversational Analytics

We need to output HTML fragment with sections: About the role? Actually the posting includes intro paragraphs about Ro, then "The Role" etc. We need to use

for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must only include sections when posting has real specific content. We have content about role description (What You'll Do) and What You'll Bring (requirements/qualifications). Also salary range given. Benefits mentioned: "competitive equity and benefits package". So we can include Benefits section (maybe mention equity and benefits). Pay section: we have salary range. Schedule not mentioned, so omit. Also we have "About the role" maybe we can include a short paragraph summarizing the role? The intro paragraphs about Ro could be considered "About the role"? Actually "About the role" heading could contain description of role and mission. We'll include that. We must not repeat job title as heading. No Job ID. Remove boilerplate like EEO etc. Also remove application instructions, privacy policy, accommodation contact, etc. We need to preserve all substantive info. So we need to include the mission paragraphs, the role description, responsibilities (What You'll Do), qualifications (What You'll Bring), nice-to-haves maybe as part of Requirements or Skills. Also include Pay section with salary range. Benefits section with equity and benefits package. We must not include filler like "commensurate with experience". Not present. We need to use

• for any list of duties/requirements/benefits. So we need to convert the bullet-like sentences into lists. Let's extract: Mission/intro: "Join Tech @ Ro to build the future of healthcare, from the ground up! At Ro, we believe that when people achieve their health goals, they can achieve their life goals. The highest-leverage way to move society forward is to give people their health, and the current healthcare system isn’t built to do that. It was built to bill, not to serve patients. We’re building a new system. One where the patient is in control. One designed from scratch for the digital age. At Ro, technology isn’t just a function… It's core to how we deliver care. We’ve built a vertically integrated healthcare platform that connects telehealth, diagnostics, pharmacy, and logistics into a seamless, end-to-end experience for millions of patients. …and we’re just getting started. As part of Tech @ Ro, you’ll work on systems that operate at scale, with an opportunity to: Solve complex, high-concurrency problems across a full-stack platformBuild and ship quickly with tight feedback loops and real-world impactOwn systems end-to-end, from architecture to production performanceWork alongside experienced operators, technical leaders, and cliniciansHelp define how modern healthcare should be delivered We’re a performance-driven team with a strong sense of ownership and urgency. We move fast, learn quickly, and hold a high bar for what we build, and do so with a big heart — because patients depend on it. If you’re motivated by impact, scale, and the chance to help lead the patient revolution, come build with us." That's substantive; we can put under

  About the role

  with paragraphs. Then "The Role 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 building data models/semantic models, documentation, context, and evaluations to strengthen our LLMs’ ability to consistently achieve the correct answers, and 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." That could be part of About the role or Responsibilities. We'll treat as Responsibilities maybe. Then "What You'll Do" list: - 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 These are duties; we can put under

  Responsibilities

  with
  . Then "What You’ll Bring to the Team": - 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 Nice-to-haves: - Experience with AI evaluation of LLM tools - Experience developing data pipelines and processes - We are open to data analysts with demonstrable interest and project experience who are looking to make the transition to analytics engineer We can combine Requirements/Qualifications/Skills. The instruction says use headings like Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to decide which to use. We have responsibilities list. We have qualifications (experience, skills). We have skills (SQL, BI tools, communication, problem solving). We could put all under Requirements or Qualifications. Perhaps we can have

  Requirements

  for the mandatory items, and

  Nice-to-haves

  but that's not in allowed headings; we could fold into Requirements or Skills. Since we must only use allowed headings, we can put all under

  Requirements

  and maybe separate into

  Skills

  for technical skills. But we must not create sections with filler. We have content for both. We could do:

  Requirements

  with the mandatory items (4+ years experience, hands-on LLMs, expert SQL, BI tools experience, strong communication/teaching, strong problem solving, analytical aptitude, numerical dexterity, demonstrated track record).

  Skills

  maybe list SQL, BI tools, LLMs, communication, teaching, problem solving. But that duplicates. Better to keep one Requirements section that includes both mandatory and nice-to-haves? But nice-to-haves are not required; still we can include them as part of Requirements but note they are nice-to-have. That's okay. Alternatively we could have

  Qualifications

  for the experience and education, and

  Skills

  for technical skills. Let's see. We have: "4+ years of full-time working experience in quantitative analysis roles, with a portion of that time focused on data modeling in DBT" -> qualification. "Hands-on experience using LLMs for coding and analytics, going beyond asking simple questions and building data products through LLM workflows" -> skill. "Expert-level SQL skills" -> skill. "Experience using BI tools (ours are Hex and Looker) to effectively convey information" -> skill. "Strong communication and teaching skills" -> skill. "Strong problem solving skills, analytical aptitude, and numerical dexterity" -> skill. "Demonstrated track record of project ownership" -> qualification. Nice-to-haves: "Experience with AI evaluation of LLM tools", "Experience developing data pipelines and processes", "We are open to data analysts with demonstrable interest and project experience who are looking to make the transition to analytics engineer" -> could be qualifications/skills. Thus we can have:

  Qualifications

  with 4+ years experience, demonstrated track record, open to analysts transitioning, etc.

  Skills

  with LLMs experience, expert SQL, BI tools (Hex/Looker), communication/teaching, problem solving, analytical aptitude, numerical dexterity, AI evaluation experience, data pipeline experience. But we must avoid duplication. It's okay if some items appear in both? Better to keep distinct. Let's decide: We'll have Responsibilities, Requirements (maybe combine qualifications and skills), Benefits, Pay. Given the instruction: "Prefer a few substantive sections over many thin ones." So maybe we just have About the role, Responsibilities, Requirements, Benefits, Pay. That's 5 sections. We'll put all candidate qualifications under Requirements (including experience, skills, nice-to-haves). That's substantive. Thus:

  About the role

  ... mission paragraphs ...

  Responsibilities

  • ...
  ...

  Requirements

  • 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 (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
  • Nice-to-haves: Experience with AI evaluation of LLM tools; Experience developing data pipelines and processes; Open to data analysts with demonstrable interest and project experience looking to transition to analytics engineer
  But the nice-to-haves line is a bit messy; we could split into separate li items. Better: separate li for each nice-to-have. Thus:
  • Experience with AI evaluation of LLM tools (nice-to-have)
  • Experience developing data pipelines and processes (nice-to-have)
  • Open to data analysts with demonstrable interest and project experience who are looking to make the transition to analytics engineer (nice-to-have)
  Now Benefits: "competitive equity and benefits package". Also maybe mention recognition as top workplace etc. That's also substantive but could be considered Benefits? The recognition is more about company accolades; could be part of About the role? But we already have About the role with mission. We could add a Benefits section with equity and benefits package, plus maybe mention recognitions? The instruction: include Benefits section only if posting actually states them. It does state "competitive equity and benefits package". Also mentions recognitions but those are not benefits per se; they are accolades. Could be included in About the role but we already have that. We'll keep Benefits short. Pay: salary range $137,300 to $166,000. We must not include filler like "commensurate with experience". Not present. We must not include boilerplate like EEO etc. Remove those paragraphs. Now produce HTML fragment. Make sure to wrap each section in

  and then content. No extra tags like unless needed? Not required. We'll output