Technical Business Analyst | Revyse

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11d•$80,000 - $100,000

About The Position

Revyse is seeking a Technical Business Analyst to join their team. This role is crucial for optimizing the context and documentation that feeds their AI-powered ticket generation system and engineering teams. The company operates without traditional sprints, utilizing cross-functional pods and AI to draft tickets, with a focus on moving fast by ensuring the right work is the easiest to pick up. The domain is complex, involving intricate insurance requirements that vary by trade, scope, and state, as well as customer-specific compliance rules. The Technical Business Analyst will be responsible for understanding and documenting the platform's current behavior, building and maintaining reference material for AI and engineers, and reviewing tickets and specs for accuracy before development. This role also involves analyzing product data using SQL to answer questions about usage, throughput, drop-off rates, and workflow completion. You will quantify the impact of shipped work, build recurring reports for pods, and proactively identify anomalies and insights from the data. Additionally, you will create working prototypes using AI assistance to communicate ideas concretely, enabling teams to react to tangible examples rather than abstract concepts. The ideal candidate is comfortable operating without extensive process scaffolding and possesses strong analytical honesty and written clarity.

Requirements

3+ years as a business analyst, technical analyst, product analyst, data analyst, or in product operations, working closely with engineers.
Strong SQL skills, including the ability to write own queries, understand join impacts on row counts, and sanity-check results.
Ability to read a database schema and infer product behavior from it.
Experience using AI as a daily tool, including structuring context for reliable output, iterating on prompts, and identifying confidently incorrect model outputs.
Ability to build a rough working prototype with AI assistance that is good enough for team reaction.
Excellent written communication skills.
Analytical honesty, including quantifying rather than characterizing, naming assumptions, and investigating reconciling discrepancies.
Comfort operating without process scaffolding.
Comfort saying “not this week, here's why” when faced with competing priorities.

Nice To Haves

B2B SaaS experience with enterprise customers.
Experience with compliance- or workflow-heavy products.
Python for analysis.
Experience maintaining documentation that AI tooling depends on.

Responsibilities

Understand and document the platform's current behavior, including workflows, exception paths, rules, and undocumented behavior.
Build and maintain reference material for AI tooling and engineers, ensuring accuracy as the product evolves.
Review tickets and specifications against reality before development begins, focusing on edge cases, compliance rules, and customer-specific commitments.
Capture acceptance criteria, edge cases, failure behavior, and explicit non-goals to enable pods to build features without extensive meetings.
Answer product questions using SQL against real data, analyzing metrics such as usage, throughput, drop-off, exception rates, workflow completion, and turnaround times.
Quantify the impact of shipped work by measuring its effect on key metrics.
Build and maintain recurring reports for engineering pods.
Proactively identify and surface insights from data, noting distributions, outliers, and discrepancies.
Build working prototypes using AI assistance to communicate ideas and facilitate team feedback.
Build small internal tools for personal or team use when it is more efficient than requesting them.
Clearly communicate intent to engineers through prototypes, which serve as the argument for the work, not the final implementation.