Job Description & How to Apply Below
On the heels of market expansion and growth, Resonate is hiring an experienced Data Analyst to join our Data Analytics team and support our clients. Resonate is an Australian Scale-up organization that has an enterprise Customer Experience (CX) platform (SaaS). The Resonate Voice of Customer and Voice of Employee platform leverages the latest technology including machine learning, text analytics, data visualization etc.
to deliver actionable insights to leading companies.
The role:
We’re looking for a technically strong Data & Insights Analyst who can operate across both advanced analytics and insight delivery. You will work with large, complex CX datasets, contribute to machine learning and LLM-driven use cases, and turn findings into clear, decision-ready insights for clients.
In this role you will:
Analyze large volumes of customer and employee experience data to uncover trends, drivers, and performance gaps.
Design and maintain scalable data workflows for extraction, transformation, validation, and reporting.
Apply advanced statistical and machine learning techniques, including LLM-based approaches, to extract insight from structured and unstructured data.
Partner with Customer Success team to define insight questions and translate analysis into clear, actionable narratives.
Build analytical outputs and visualizations that balance technical rigor with commercial clarity.
Contribute to the ongoing evolution of Resonate’s analytics and AI capability through experimentation and continuous improvement.
Apply project management practices to track progress and ensure the timely delivery of analytical outputs.
Requirements
What we are looking for:
2–4 years of experience in a data, analytics, insights, or applied data science role, ideally in a client-facing or commercial environment.
Strong technical capability across data analysis and modelling, with experience using analytical tools and visualization platforms to deliver insight.
Exposure to text analytics, NLP, and/or LLM-driven approaches, with an interest in applying these techniques to real-world business problems.
Proven ability to translate technical analysis into clear, decision-ready insights that drive action.
A degree in quantitative discipline such as Statistics, Data Science, Computer Science, or a related field.
Confident communicating with both technical and non-technical stakeholders, and comfortable tailoring messages to different audiences.
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