Product Data Science Lead

About This Opportunity

Our talent team is representing a confidential cybersecurity SaaS organization in their search for a Product Data Science Lead based in Australia. This is a fully remote, permanent position for an experienced product analytics professional who thrives in high-growth environments.

Our client is scaling rapidly following significant recent funding, processing billions of risk signals daily through their platform. They're building the analytics foundation that will power both human decision-making and AI-driven insights across their product portfolio.

This is a ground-up build opportunity: you'll own product analytics end-to-end, creating the governed semantic layer and metric definitions that will serve as the foundation for self-service analytics. The models you create will be queried by both stakeholders and AI agents, making clarity and rigor essential.

Responsibilities

• Generate actionable insights from complex product and usage datasets to inform roadmap prioritization, feature investment, and engagement strategy
• Design and maintain product KPIs and engagement milestones covering activation, onboarding, and ongoing platform engagement
• Build comprehensive product funnel analytics across onboarding, activation, feature adoption, and retention
• Partner with data engineering to construct foundational product data assets using dbt, creating a governed metrics layer
• Develop self-service dashboards and conversational analytics capabilities for product stakeholders
• Conduct hands-on technical analysis to diagnose product challenges including onboarding drop-off, feature underperformance, and churn risk
• Translate product usage signals into adoption plays, health scores, and expansion/renewal risk indicators for Sales and Customer Success teams
• Collaborate closely with Product Managers, Operations, Design, Engineering, and Success teams to deliver high-impact analytics initiatives

What We're Looking For

Required Experience and Skills:

• 4+ years delivering analytics solutions for Product teams within high-growth SaaS companies
• Strong product analytics domain knowledge covering activation, engagement, feature adoption, retention, and north star metrics frameworks
• Statistical rigor including understanding of significance, confidence intervals, sample size, variance, and cohort analysis
• Fluency in how Sales and CS teams consume product usage data for health scoring, expansion signals, and renewal risk assessment
• Proven ability to translate ambiguous product requirements into structured dbt models and clear metric definitions
• Strong understanding of modern data infrastructure including cloud data warehouses (BigQuery), ETL/ELT tools, dbt development, and visualization platforms (ThoughtSpot, Omni, Looker)
• Exceptional business acumen with ability to identify KPIs and translate data into strategic insights
• Excellent communication skills for both technical and non-technical audiences, with ability to influence decision-making
• Hands-on experience authoring dbt models and creating BI infrastructure
• Fluency leveraging AI/LLM tools to accelerate analysis, code development, and documentation

Advantageous Experience:

• Data science or AI engineering background, particularly with engagement scoring, causal inference, or building LLM agent query layers
• Hands-on experience with product analytics tools (Segment, Mixpanel, Amplitude) and CS platforms (HubSpot, Salesforce)
• Strong grasp of B2B SaaS metrics including NRR/GRR, activation, time-to-value, product-qualified leads, and expansion/churn drivers

Additional Requirements:

• Must be based in Australia and authorized to work without sponsorship
• National police history check and reference checks will be required before commencement

How We Work With You

When you apply through Get A Job.ai, one of our recruiters will screen your application and conduct an initial conversation about your background and the role. If there's a strong match, we'll submit your profile to our client for consideration. Please do not attempt to contact the employer directly—all communication should flow through our recruitment team to ensure a smooth process.

Pay

Compensation details will be discussed during the screening process based on experience and qualifications.

Equal Employment Opportunity: Get A Job.ai is committed to creating a diverse and inclusive environment. We provide equal employment opportunities to all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.