Business Analyst

Job Description

Job Description

Why this role exists:

Our Client is scaling rapidly and setting the standard for modern home services. Our

AI-enabled contact centers live across dozens of markets and are moving millions in

revenue. Recognizing its importance, our CRO has personally owned the AI strategy

and rollout, and the next phase is about accelerating impact. This is a greenfield

scale-up (not brand new): you'll build on proven workflows, tighten feedback loops, and

help turn a strong foundation into a durable growth engine.

KEY RESPONSIBILITIES

• Live QA & Guardrails: Monitor AI-initiated calls (cancellations, reschedules, supervisor requests); flag edge cases and ensure correct handling.
• Automation & Integration Building: Build and maintain lightweight automations, scripts, and integrations (e.g., API connections, Zapier/Make, Google Apps Script) that support AI-driven workflows and remove manual busywork.
• Stakeholder Workflow Review & Training: Establish new operational workflows, perform routine integrity audits, collect feedback, and iterate on process improvements; train stakeholders as needed.
• Call Listening & Annotation: Review recordings daily; tag misclassifications, communication issues, and coaching moments; propose fixes.
• Data Hygiene & Tracking: Accurately document outcomes; maintain clean logs; build and update lightweight trackers/dashboards (Google Sheets, Excel, or simple internal tools).
• KPI Rhythm: Publish quick daily notes on what changed and what to try next; surface trends impacting contact rate, conversion, and cancellation rate.
• Continuous Improvement: Collaborate with the CRO, AI ops, and third-party vendors to iterate prompts, routing, and workflows; use AI coding tools to prototype fixes and validate changes with small A/B tests before scaling.
• Documentation & Communication: Create and maintain documented workflows, processes, and lightweight technical scripting for all projects under scope; communicate with stakeholders across the business.
• Escalation Judgment: Step in when customer needs fall outside standard AI behavior; protect CX, document the exception, and codify the new rule.

SUCCESS METRICS (PRIMARY KPIS)

• Contact Rate: More customers reached on the first attempt.
• Conversion: Higher book rate from AI-assisted interactions.
• Cancellation Rate: Fewer post-booking cancellations.
• Automation Reliability: Fewer manual workarounds and errors in owned workflows, trackers, and integrations.
• Additional KPIs TBD.

CAREER PROGRESSION

This is an early-stage position. This person will help define the operating model, SOPs, dashboards, and lightweight automation stack for Southwind's AI-enabled contact centers, with direct visibility to the CRO and priority projects. As the function matures, the role may expand in scope to include ownership of a KPI, market cluster, key initiative, or a broader automation platform this person helped build.

QUALIFICATIONS

• Bachelor's degree required.
• 1+ years of experience in a professional, data-driven setting.
• Clear, concise written and verbal communication; comfortable translating call nuance into actionable fixes.
• Attention to detail and a QA mindset; enjoys checklists and pattern-spotting.
• Intermediate spreadsheet skills (filters, lookups, data validation) in Google Sheets or Excel.
• Comfort building simple automations or scripts (e.g., Zapier, Make, Google Apps Script, or basic Python/JavaScript) is a plus, not a requirement.
• Comfort with technology and learning new tools quickly.
• A customer-service mindset: accuracy, empathy, operational excellence.

NICE-TO-HAVES

• Salesforce, Google Workspace power-user skills, Dialpad or similar telephony, QA platforms, or call recording tools.
• Basic prompting/LLM concepts; familiarity with AI coding tools (GitHub Copilot, Claude, ChatGPT, Cursor, etc.).
• Basic API/webhook familiarity or SQL exposure.

CANDIDATE ATTRIBUTES

This is a roll-up-your-sleeves builder role, not a senior enterprise-architecture position. Candidates should be excited to get into the details — listening to calls, fixing workflows, building small automations, and iterating quickly — using AI as an accelerant rather than working at a high level of abstraction.