Data Scientist

Megaport is the global leader in Network as a Service (NaaS), transforming how businesses connect to the cloud, data centers, and each other. Publicly listed on the Australian Stock Exchange and partnered with major tech companies like Amazon, Microsoft, Google, Oracle, and IBM, we operate across Asia-Pacific, Europe, and the Americas with a collaborative, customer-focused culture.

About the role

We are seeking an experienced, business-oriented Data Scientist to scale advanced analytics and operational intelligence capabilities across the Revenue organization. This role partners closely with Revenue Operations, Data Engineering, Finance, Systems, and Commercial leadership to improve forecasting, operational visibility, AI readiness, and data-driven decision-making. You will build advanced analytics supporting Sales Operations, Revenue Operations, forecasting, customer insights, operational efficiency, and AI initiatives. The ideal candidate combines strong technical and analytical expertise with the ability to translate complex data into actionable business insights.

Responsibilities

• Develop predictive forecasting models and pipeline analytics frameworks
• Analyze sales productivity, customer behavior, operational efficiency, and revenue trends
• Build scalable dashboards, models, and operational intelligence solutions
• Partner with Revenue Operations and Finance teams to improve KPI governance and reporting consistency
• Support AI readiness initiatives through data quality analysis and modeling
• Collaborate with Data Engineering teams to improve GTM data architecture and integration quality
• Identify operational inefficiencies and recommend data-driven process improvements
• Develop analytical frameworks supporting marketplace, channel, and consumption-based business models
• Support executive decision-making through advanced reporting and business analysis
• Assist with data governance, metric standardization, and forecasting transformation initiatives
• Build models supporting customer expansion, renewals, and churn analysis

Requirements

• 5+ years of Data Science, Analytics, or Revenue Intelligence experience
• Strong SQL, Python, and statistical modeling expertise
• Experience working with large operational and sales datasets
• Experience building forecasting and predictive analytics models
• Strong data visualization and dashboarding capabilities
• Experience partnering with business stakeholders and executive teams
• Strong understanding of SaaS or technology business models
• Ability to translate technical findings into business recommendations

Benefits

• Flexible working environments
• Birthday Leave, 12 weeks of parental leave (after 12 months continuous service), and 5 days of study leave
• Creative, fun, and contemporary work environments
• Motivated team of industry experts and plenty of learning opportunities
• Celebrated success with internal awards programs
• Health and wellness program
• Generous performance bonus structure