Working at Atlassian

Atlassian can hire people in any country where we have a legal entity. Assuming you have eligible working rights and a sufficient time zone overlap with your team, you can choose to work remotely or return to an office as they reopen (unless it’s necessary for your role to be performed in the office). Interviews and onboarding are conducted virtually, a part of being a distributed-first company.

Atlassian is looking for a Machine Learning Scientist specializing in paid user acquisition to join our Core Machine Learning team based in Mountain View, CA. The Core Machine Learning team builds and deploys ML modeling solutions to improve revenue and increase our active user base. This is accomplished by driving the complete end-to-end ML development cycle. We offer a unique opportunity to work in a collaborative environment, implementing the latest machine learning techniques, including NLP modeling, to solve tough, yet unique problems in the marketing space.

Your future team

The Core Machine Learning team at Atlassian is an agile team of machine learning scientists and engineers. It works cross-functionally across the organization and provides machine learning infrastructure and modeling applications to the business and partner analytics teams, with the tasks to pursue machine learning opportunities that generate revenue or user base improvements. The team is split geographically between the US and Sydney, supporting stakeholders across the regions. The team is highly nimble, with a focus on velocity between conceptualization and initial output, and on business impact.

On the first day, we'll expect you to have

• Bachelor or higher degree in a quantitative subject (Statistics, Mathematics, Computer Science, Operations Research, or relevant work experience)
• Industry or academic experience in the data science or machine learning domain
• Expertise in Python with and the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. AWS, Databricks)
• Explain data science and machine learning concepts to diverse audiences and create a compelling story
• Agile development mindset, appreciating the benefit of constant iteration and improvement

It's Great, But Not Required, If You Have

• 2+ years of professional experience with developing large-scale machine learning applications
• Strong knowledge of statistics, machine learning, and NLP
• Experience working in a consumer or B2C space for a SaaS product provider, or the enterprise/B2B space
• Experience with end-to-end software development life-cycle