Business Analyst (Growth)
Description
Mayflower is a technology company building large-scale entertainment products for a global audience. Our platforms serve millions of users worldwide and rank among the top-50 most visited websites globally. For more than 10 years, we’ve been creating reliable, high-performance solutions at the intersection of product, engineering, and entertainment.
We are looking for a Business/System Analyst to join a team for our Growth stream.
Job Responsibilities
Requirements Elicitation & Specification
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Gather, structure, and validate requirements collaboratively with Product, Engineering, Design, and QA.
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Translate product hypotheses and business goals into clear, testable artifacts such as user stories, epics, acceptance criteria, and business rules.
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Ensure task descriptions are clear and detailed for development and QA, including scenarios, parameters, constraints, and necessary checks.
System Analysis & Architecture
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Dive deep into technical details, demonstrating an understanding of data structures, APIs, integrations, system constraints, and microservice architecture to communicate with engineers on their level.
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Participate in architectural analysis alongside developers and architects.
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Deeply detail technical tasks to reduce the workload on architects and developers.
Requirements Lifecycle & Delivery Support
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Maintain requirements throughout the delivery cycle, managing changes and documenting decisions and assumptions.
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Support developers and QA engineers in clarifying context and validating shipped features against the intended requirements.
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Serve as the primary bridge between Product and Engineering, driving alignment on scope, risks, dependencies, and constraints.
Knowledge Base Management & AI Preparation
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Create and maintain a clear, structured, and searchable knowledge base detailing product behavior, business logic, APIs, data, admin pages, and system relationships.
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Actively eliminate product knowledge gaps by extracting missing information from the Product, Dev, and QA teams and documenting it to prevent recurring questions.
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Update documentation immediately following releases to accurately reflect the actual system behavior.
Prepare knowledge for LLMs:
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Detail architectural and business logic so it can be effectively used to build a vector knowledge base for LLMs. Organize documentation so that AI can accurately answer system queries, and continually refine the knowledge base to address gaps the AI cannot answer.
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Utilize AI tools (like ChatGPT, Gemini, or Claude) to accelerate your daily tasks—such as drafting requirements, checking consistency, and generating scenarios—while applying rigorous verification and accountability for the output's correctness.