
Marketing Data Science Lead
UpGuard
Marketing Data Science Lead
UpGuard is seeking a Marketing Data Science Lead to join their remote team in Brisbane, Australia. The role involves driving marketing analytics, building attribution frameworks, and creating data models to support the marketing team's growth. The ideal candidate has 4+ years of experience in analytics for marketing in a high-growth SaaS company, with strong skills in dbt, data warehousing, and AI tools.
Marketing Data Science Lead
UpGuard is seeking a Marketing Data Science Lead to join their remote team in Brisbane, Australia. The role involves driving marketing analytics, building attribution frameworks, and creating data models to support the marketing team's growth. The ideal candidate has 4+ years of experience in analytics for marketing in a high-growth SaaS company, with strong skills in dbt, data warehousing, and AI tools.
Salary
Core Qualifications
Technical (Must-have)
Soft Skills
Preferred Qualifications
Technical (Nice-to-have)
Key Responsibilities
- Generate compelling and actionable insights from complex, multi-source marketing data sets that directly inform channel investment, campaign design, and pipeline strategy.
- Establish strong collaborative relationships with marketing leaders and operators across demand gen, partner, field, product marketing, and brand, delivering high-impact analytics initiatives that translate loose, evolving requirements into clear deliverables.
- Design, build, and maintain the attribution framework for UpGuard – spanning first and multi-touch attribution and incrementality testing – and clearly communicate the trade-offs and assumptions behind each lens.
- Develop a deep, first-principles understanding of channel logic across paid media, organic, content, lifecycle, partner, and field, and build the metrics, models, and dashboards that let each program owner self-serve their performance.
- Partner with the data engineering team to design, construct, and maintain foundational marketing data assets – translating loose marketing requirements into well-specified dbt models and a governed semantic/metrics layer that both humans and AI agents can reliably query and traverse.
- Partner strategically with marketing stakeholders to provide robust self-service and conversational and agentic analytics capabilities, using design thinking principles to build user-friendly dashboards for funnel performance, channel ROI, partner sourced pipeline, and field event attribution.
- Personally conduct thorough, hands-on, technical analysis to diagnose and solve the most significant marketing challenges – from channel saturation and diminishing returns to lead quality decay and campaign cannibalisation.
- Provide ongoing operational support to the commercial growth of the organisation, connecting marketing investment to pipeline, ARR, and payback in ways that finance and the executive team trust.