Business Analyst

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

• Gather, structure, and validate requirements collaboratively with Product, Engineering, Design, and QA.
• Translate product hypotheses and business goals into clear, testable artifacts such as user stories, epics, acceptance criteria, and business rules.
• Ensure task descriptions are clear and detailed for development and QA, including scenarios, parameters, constraints, and necessary checks.

System Analysis & Architecture

• 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.
• Participate in architectural analysis alongside developers and architects.
• Deeply detail technical tasks to reduce the workload on architects and developers.

Requirements Lifecycle & Delivery Support

• Maintain requirements throughout the delivery cycle, managing changes and documenting decisions and assumptions.
• Support developers and QA engineers in clarifying context and validating shipped features against the intended requirements.
• Serve as the primary bridge between Product and Engineering, driving alignment on scope, risks, dependencies, and constraints.

Knowledge Base Management & AI Preparation

• Create and maintain a clear, structured, and searchable knowledge base detailing product behavior, business logic, APIs, data, admin pages, and system relationships.
• Actively eliminate product knowledge gaps by extracting missing information from the Product, Dev, and QA teams and documenting it to prevent recurring questions.
• Update documentation immediately following releases to accurately reflect the actual system behavior.

Prepare knowledge for LLMs:

• 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.

• 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.