About the company:

Seeing Machines has developed the world’s most advanced human data-driven technology which enhances transport safety by dramatically reducing fatal accidents every day. We’re on a mission to achieve zero transport fatalities.

With at least 1 million cars on the road using our state-of-the-art operator monitoring technology developed by the passionate team at Seeing Machines, we provide real-time protection from distraction and drowsiness-related driving events. Seeing Machines works with many of the world’s leading brands (including General Motors, Mercedes Benz, Qantas, Caterpillar, Toll) across the transport sectors automotive, commercial road transport (Fleet), and aviation.

Position Summary:

The Commercial Finance Analyst is the team’s modelling and forecasting specialist. The role exists to lift the quality and speed of commercial decision support by building robust, driver-based models, maintaining rolling forecasts, and converting performance data into clear, decision ready‑insight.

Our vision is to build a world‑class commercial finance function that is a strategic partner to the business by:

• Driving accountability and performance across all business units, through insightful, standardised reporting and analysis.

• Embedding governance and structure for significant commercial decisions, ensuring speed, rigour and compliance.

• Providing corporate troubleshooting, problem solving and solutions-oriented advice to executives and business leaders.

• Delivering automation and intelligent tooling so financial and operational insights are available instantly, closing the gap between close and insight.

Lifting finance capability and culture to contemporary best practice, with transparency, collaboration and continuous improvement.

Key Responsibilities:

1) Budget and Monthly Performance Review

• Support the design and execution of the annual budget and Monthly Performance Review cadence, with a focus on modelling integrity and decision relevance.

• Build and maintain the key drivers and assumptions underpinning revenue, margin, cost, headcount and investment outcomes.

• Prepare scenario options and sensitivities to support informed trade‑offs during planning cycles.

2) Forecasting and scenario modelling

• Develop and maintain dynamic, driver‑based models (Adaptive Planning and Excel) to support rolling forecasts and forward‑looking scenario analysis.

• Produce “what‑if” modelling to assess the financial impact of changes in volume, pricing, mix, cost structure, FX, terms and timing.

• Identify emerging risks and opportunities early through trend analysis and sensitivity testing.

3) Performance analysis and management reporting

• Analyse actual performance against plan and forecast, identifying root causes and underlying drivers.

• Contribute to standardised management reporting, including clear executive‑level commentary and concise narratives for non‑financial stakeholders.

4) Strategic business partnering

• Act as an analytical partner to functional and BU leaders, providing structure, insight and financial context to commercial decisions.

• Constructively challenge assumptions and proposals using evidence‑based analysis.

• Support workforce planning through labour cost analysis, headcount modelling and affordability trade‑offs.

5) Commercial papers and investment cases

• Support the Head of Commercial Finance in preparing modelling and analysis for material initiatives, ensuring assumptions, options and risks are explicit and testable.

• Maintain strong model discipline, including version control, documented assumptions and transparent logic suitable for executive scrutiny.

6) Ways of working

• Build models and analysis that are repeatable, well‑documented and scalable, avoiding bespoke or opaque outputs.

• Work closely with the Finance Systems Analyst to ensure modelling outputs align with agreed data definitions, validation controls and reporting sources.

• Proactively identify opportunities to automate modelling, analysis and insight generation (including appropriate use of AI‑enabled tools) to improve efficiency, consistency and decision quality.