ఉద్యోగ వివరణ

Role overview

This opportunity is being shared on behalf of a partner organisation, which will handle applications and the next steps in the hiring process. The partner is seeking a Product Analyst located in Australia.

The role is central to product decision-making, using customer behaviour and platform data to generate practical insights that shape product strategy and roadmap choices.

You will examine how users interact with a complex SaaS product, spotting adoption trends, points of friction, and signals of retention that help guide product improvements.

Working alongside Product leadership and other cross-functional partners, you will help keep decisions anchored in evidence rather than assumptions.

The environment is fast-paced and strongly data-oriented, with regular exposure to senior stakeholders and product strategy conversations.

You will contribute to building stronger product intelligence capabilities across the business, improving clarity around what drives value for users.

This position suits someone who enjoys combining rigorous analysis with visible influence on product direction and business results.

It is a collaborative setting where insights are expected to lead to concrete product changes.

Key accountabilities

Take ownership of analysing user behaviour across the product, including journeys, engagement trends, session depth, and usage frequency across customer segments.
Track feature performance, adoption levels, and experiment outcomes to understand what enhances or constrains product value.
Run cohort, funnel, retention, and expansion analyses to uncover behaviour patterns and help forecast customer lifecycle outcomes.
Pinpoint friction, drop-offs, and weak-performing areas, then turn those findings into clear, actionable recommendations.
Set up, monitor, and maintain core product KPIs while keeping reporting consistent, accurate, and dependable across layers.
Continuously support Product leadership with analysis that informs roadmap choices and helps surface product health risks early.

Requirements

At least 3-6+ years of experience in product analytics, SaaS analytics, or other data-led product environments.
Strong command of SQL, data modelling, and analytics platforms, along with practical experience handling large datasets.
Hands-on experience with cohort analysis, funnel analysis, retention modelling, and interpretation of behavioural data.
Ability to convert complex data into concise, executive-level insights that can shape product decisions.
Experience partnering closely with Product Managers and cross-functional teams in high-growth settings.
Strong quantitative judgement, structured problem-solving, and comfort working with incomplete or changing data.
Well-suited to fast-moving, product-led organisations where insights directly affect execution.

Benefits and compensation

Competitive pay aligned with experience and prevailing market benchmarks.
Fully remote working setup with opportunities to collaborate globally.
Flexible work arrangements that support balance between work and personal life.
Direct exposure to senior product leadership and the chance to shape roadmap decisions.
Experience with large-scale SaaS product analytics and strategic decision-making.
A dynamic, rapidly growing environment focused on data-driven innovation.

How the hiring process works

The application process uses an AI-assisted matching approach to review candidates quickly, objectively, and fairly against the role’s core requirements. The system identifies the strongest matches, and that shortlist is then passed directly to the hiring company. Final decisions, including interviews and assessments, are handled by the company’s internal team.

Privacy and data processing

By applying, you agree that the recruitment partner may process your personal data to assess your candidacy and share relevant details with the hiring employer. This is based on legitimate interest and pre-contractual steps under applicable data protection laws, including GDPR. You may request access, correction, deletion, or objection at any time.

Artificial intelligence tools may also be used to support parts of recruitment, such as reviewing applications, analysing resumes, or checking responses for possible inconsistencies or verification signals. These tools assist the recruitment team but do not replace human judgement. Final hiring decisions are always made by people. For more information about data handling, you may contact the recruiter.

Product Analyst