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Megaport

Data Scientist

Megaport is hiring a Data Scientist in Brisbane, Australia. Level rates it ; you can apply on Megaport.

Level's read on this job

  • Little AI ●○○○ is how Level rates this data scientist role: aI is not part of the work.
  • Megaport has 60 other open roles on Level.

AI in this role

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.

 

What You’ll Be Doing

  • 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

What We Are Looking For

  • 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

What We Offer

  • 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

If you have any questions, please reach out to Megaport's Talent Acquisition Team at Careers@megaport.com   NOTE: All Megaport business correspondence is conducted via our business email accounts (@megaport.com). If you have any concerns, please reach out to Megaport's careers team careers@megaport.com directly and we will verify the legitimacy of any communication. Megaport will not ask you to create an account via Microsoft teams, and does not associate with any email accounts under "@megaportau.com".   All applications will be treated in confidence. Please see Part 2 of our Privacy Policy to see what information Megaport collects from job applicants, why, and how we store and use it. Note that you’re entitled to know what personal data of yours Megaport holds, to request updates, rectification, and in some circumstances restriction or deletion thereof if you object (you being entitled to withdraw your consent to our holding your information at any time). Please see Part 5 of our Privacy Policy for more details on this and how to contact Megaport's data protection officer if you have any further privacy-related questions. Candidates who meet the selection criteria will be invited to attend an interview. Strictly no Recruitment Agencies.

How we rate this

Data Scientist at Megaport rates 33 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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