Data Scientist

About Megaport We’re not your typical tech company – and we don’t want to be. Megaport is the global leader in Network as a Service (NaaS), and has transformed the way businesses connect to the cloud, data centers, and each other. We’re publicly listed on the Australian Stock Exchange and partnered with the biggest names in tech like Amazon, Microsoft, Google, Oracle, IBM, and more. Headquartered in Brisbane with a crew of over 600 people spread across Asia-Pacific, Europe, and the Americas, our employees enjoy an environment that is collaborative, supportive, and (actually) fun.

Our Team Culture We’re a team of problem solvers, pixel pushers, code slingers, and cloud fanatics. Culture is more than a poster on the wall here – collaboration beats hierarchy, curiosity fuels our growth, and everyone’s voice matters. We take our work seriously, but not ourselves. We work across time zones to execute on our global vision, trust each other to get things done, and never compromise our values for commercial gain. Most importantly, we place our customers at the center of everything we do.

We’re committed to increasing representation in the tech industry and welcome applicants from all backgrounds. Don’t meet every requirement? That’s okay. If you’re excited about this role, we encourage you to apply.

The Role Megaport is seeking an experienced and business-oriented Data Scientist to help scale advanced analytics and operational intelligence capabilities across the Revenue organization. This Data Scientist will partner closely with Revenue Operations, Data Engineering, Finance, Systems, and Commercial leadership teams to improve forecasting, operational visibility, AI readiness, and data-driven decision making. This role will help build advanced analytics capabilities 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.

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

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

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

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