FP&A Analyst (AI & Automation)

This role exists to make Asurion APAC’s finance function radically more productive through AI. You will sit at the intersection of FP&A and applied AI-- building, deploying and embedding AI tools that compress cycle times, automate low-value work, and elevate the quality of insight the team delivers to the business. Two equally weighted mandates: (1) deliver measurable productivity gains through AI-enabled FP&A workflows – forecasting, variance analysis, commentary generation, scenario modelling, deck building, and decision support; and (2) train, coach and uplift the wider APAC finance team so that every analyst, controller and country lead operates at a higher leverage point. Success is not measured in reports produced – it is measured in hours redeployed, decisions accelerated, and capability built across the function.

Key Accountabilities:

• AI productivity delivery – own the use-case backlog. Identify, prioritise and ship AI/automation use cases across the APAC finance lifecycle (close, forecast, AOP, 5Y planning, board reporting, partner reviews). Quantify the productivity uplift of every deployment – hours saved, cycle days compressed, error rates reduced – and report progress quarterly to the APAC CFO.

• Train the team – embed AI fluency across APAC finance. Run a structured enablement programme for the regional finance team: prompt engineering, tool-specific workflows (Microsoft Copilot, Claude, ChatGPT Enterprise, Python notebooks), AI-augmented Excel and OneStream, and use-case clinics. Build and maintain an internal prompt library, playbooks, and a “Finance AI Champions” network across countries.

• Build AI-augmented FP&A workflows – be the citizen developer in chief. Design and operate AI-enabled forecasting, anomaly detection, variance commentary, narrative generation, scenario modelling and slide-building workflows. Stress-test outputs for accuracy, hallucination risk, and auditability. Establish a lightweight governance frame – model selection, data handling, audit trail – that satisfies controllership, IT and Security.

• Partner with the business – own a country/function FP&A vertical. In parallel with the AI mandate, carry a live FP&A partnering load (one or two markets or functions): monthly close, forecast, variance, profitability deep-dives, and decision support. This keeps the AI build grounded in real finance workflows – not theoretical pilots.

• External benchmarking – keep us honest. Track how leading finance functions (tech, insurtech, telco, professional services) are deploying AI in FP&A. Bring back what works, kill what is hype. Maintain a rolling 12–18 month AI capability roadmap and recommend where Asurion APAC should be investing time, tools and talent.

Qualifications:

• Bachelor’s degree in Accounting, Finance, Economics, Engineering, Data Science, or a related quantitative discipline. CA/CPA welcome but not required.

• 3–5 years’ experience spanning FP&A, finance transformation or finance analytics, with a track record of shipping automation or AI projects that delivered measurable productivity gains – not pilots that died on the vine.

• Hands-on AI fluency. Daily, practical user of LLM tools (Claude, ChatGPT Enterprise, Microsoft Copilot, Gemini) for finance work. Comfortable with prompt engineering, prompt chaining, retrieval-augmented workflows, and evaluating model outputs for accuracy, bias and hallucination risk.

• Builder toolkit. Advanced Excel and Power Query, working proficiency in Python (pandas, openpyxl) and SQL. Familiarity with Power BI, OneStream / Anaplan / Hyperion, and at least one low-code automation platform (Power Automate, n8n, Zapier). Bonus: API integration, vector databases, agentic workflows.

• Teaching instinct. You explain complex things simply. You have run training sessions, written playbooks or built communities of practice – and you genuinely enjoy lifting other people’s capability rather than hoarding it.

• Finance literacy. You read a P&L, balance sheet and cash flow without a translator. You understand AOP, forecast, variance analysis, unit economics and the shape of a board pack. Mindset matters more than the ticket.

• Bias to ship, scepticism toward hype. You measure your impact in productivity gained and decisions improved – not slides produced. You can tell the difference between a real AI use case and a demo. You push back when something doesn’t make sense, and you stay curious as the technology evolves.