Machine Learning Scientist

Atlassian

  • Full Time

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.

With a sufficient timezone overlap with the team, we’re able to hire eligible candidates for this role from any location in Australia and/or New Zealand. If this sparks your interest, apply today and chat with our friendly Recruitment team further.

 

In this role, you’ll get to:

 

  • Develop machine learning algorithms to predict customer lifetime value and drive business applications using these predictions
  • Construct and refine AI algorithms to optimise our marketing and onboarding funnels
  • Employ behavioural data and insights to intelligently customize the user journey, boost engagement and purchase rates and increase our number of active users
  • Work with our seriously large volume of analytics data to understand insightful trends and behaviours
  • Craft machine learning and predictive models to drive intelligent product features
  •  

    On your first day, we’ll expect you to have:

     

  • Bachelor or higher degree (or equivalent) in a quantitative subject (statistics, mathematics, computer science, engineering or physics)
  • Industry experience in the data science or machine learning domain
  • Development experience in a programming language, Python is strongly preferred
  • Expertise in SQL, knowledge of Spark and cloud data environments (e.g. AWS, Databricks)
  • Experience developing, building and scaling machine learning models in business applications using large amounts of data. Previous experience in customer lifetime value, churn and propensity modelling is highly regarded
  • Ability to communicate and explain data science and machine learning concepts to diverse audiences and craft a compelling story
  • Focus on business practicality and the 80/20 rule; very high bar for output quality but recognise the business benefit of “having something now” vs “perfection sometime in the future”
  • Agile development approach, appreciating the benefit of review, constant iteration and improvement within a collaborative team environment
  •  

    It’s great, but not required, if you have:

     

  • Experience working in an enterprise or B2B space for a SaaS product provider, as well as the consumer or B2C space
  • Familiarity working with go-to-market (GTM), Strategy, Product and Growth teams
  • Knowledge of advanced machine learning and deep learning methods applied to digital user behaviours
  • Knowledge of A/B experimentation
  •  

    More about our Team:
    The Core Machine Learning team sits within the broader Analytics group and is tasked to pursue machine learning opportunities that generate revenue or MAU improvements. This team works cross-functionally across the organisation and provides machine learning infrastructure and modelling applications to the business and partner analytics teams. 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 conceptualisation and initial output, and laser-focused on business impact.
    Our perks & benefits
    To support you at work and play, our perks and benefits include ample time off, an annual education budget, paid volunteer days, and so much more.
    About Atlassian
    The world’s best teams work better together with Atlassian. From medicine and space travel, to disaster response and pizza deliveries, Atlassian software products help teams all over the planet. At Atlassian, we’re motivated by a common goal: to unleash the potential of every team.
    We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone’s perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.
    To learn more about our culture and hiring process, explore our Candidate Resource Hub.