Senior Product Analyst

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Product Analyst based in Australia.

This role offers the opportunity to shape product decisions through rigorous data analysis, experimentation, and research.
You will take ownership of the product metrics framework and ensure teams have reliable, consistent definitions for measuring performance.
The role combines advanced analytics, statistical methods, product research, and A/B testing to uncover opportunities and guide prioritization.
You will investigate anomalies, identify conversion bottlenecks, validate hypotheses, and translate complex datasets into actionable recommendations.
Working closely with Product and functional leaders, you will connect analytical insights to business outcomes and the company’s north-star metrics.
You will also help strengthen data quality and experimentation practices so that important product decisions are based on trustworthy evidence.
This is a high-impact opportunity for an analytical professional who enjoys solving ambiguous problems and influencing product strategy through data.

Accountabilities

• Own and continuously evolve the product metrics tree, ensuring consistent and clearly documented definitions across teams.
• Validate metrics and dashboards, write clear specifications for Data Engineering, and ensure analytical requirements are correctly implemented.
• Decompose north-star metrics into measurable components that individual teams can directly influence.
• Conduct ad-hoc investigations into metric fluctuations, anomalies, conversion drop-offs, segmentation issues, and other product performance questions.
• Identify bottlenecks, non-obvious behavioral patterns, and growth opportunities through structured data mining and analysis.
• Validate product hypotheses and work with Product teams to prioritize problems according to their potential impact on key business metrics.
• Design and evaluate A/B tests, including sample-size calculations, minimum detectable effect, test duration, randomization splits, and statistical validation.
• Perform pre-test sanity checks and verify experiment splits before analyzing results.
• Analyze experiment outcomes alongside relevant guardrail metrics and translate findings into actionable product recommendations.
• Define data-tracking requirements and identify the events and instrumentation needed to support reliable experimentation.
• Maintain an organized archive of experiments, findings, and recommendations.
• Proactively identify data-quality issues and help prevent unreliable data from influencing product decisions.
• Collaborate directly with functional and product leaders to turn analytical insights into measurable improvements.

Requirements

• Higher education in mathematics, statistics, computer science, engineering, or another technical discipline.
• Strong knowledge of mathematical statistics and probability theory, with practical experience applying statistical methods to business and product questions.
• Proven experience extracting, processing, analyzing, and visualizing data using MS SQL, Python, and Excel .
• Deep hands-on experience designing, running, and analyzing A/B tests and controlled experiments .
• Strong understanding of marketing and product metrics and demonstrated experience applying them to evaluate performance and identify growth opportunities.
• Strong analytical and problem-solving capabilities, with the ability to investigate complex or ambiguous questions independently.
• Ability to translate large or complex datasets into clear insights and practical recommendations.
• Strong attention to data quality, metric consistency, and analytical accuracy.
• Excellent communication and collaboration skills, particularly when working with Product and cross-functional stakeholders.
• Proactive mindset and ability to identify important questions and opportunities rather than simply responding to requests.

Benefits

• Fully remote, full-time work opportunity.
• Competitive compensation, with the initial salary or salary range shared during the recruitment process.
• 28 calendar days of vacation per year.
• 7 wellness days per year for personal needs, recovery, or household matters.
• Referral bonuses of up to $5,000 for successful candidate recommendations.
• 50% reimbursement for professional training, international conferences, and industry meetings.
• Corporate discounts for English-language lessons.
• Health support of up to $1,000 gross per year for employees who are not eligible for corporate medical insurance, usable toward health insurance or eligible healthcare expenses for themselves and close relatives.
• Workplace equipment and support, including reimbursement of up to $1,000 gross every three years for home-office or coworking costs, depending on location.
• Access to equipped workplaces and coworking facilities where available.
• Internal gamified recognition program allowing employees to earn rewards such as merchandise, team-building activities, and massage certificates.
• International and remote-first working environment with colleagues across different locations.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.