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 from an office (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.

Are you a Data Science practitioner with a deep toolset who values helping partners scope business problems and provide analytic solutions? Do you relish the opportunity to dive headfirst into projects and contribute to an analytics ecosystem and lead optimization across the business? If so, this role is for you!

As a Principal Data Scientist on our Customer Support Services team, you will partner with important business domains, focusing on some of the most exciting challenges Atlassian faces.

Some examples of what you'll be doing:

• Work with a team to improve efficiency in a scaling customer support environment, bringing analytic capabilities and insights to bear
• Build operationally improving machine learning solutions including automation, predictive models, segmentation, anomaly detection, and optimization tools
• Work with large amount of text and customer engagement data to help build scalable analytic solutions
• Work with Software Engineering teams to build ML micro-services to integrate analytic solutions into business processes
• Forecast important outcomes to the business using different predictive capabilities and help guide better decision making
• Promote ML adoption and usage in an operational business
• Measure the growth of ML and AI applications on results.
• Develop partnerships with business and operations leaders

Some skills and tools you'll use are:

• DS: NLP, Classification, Anomaly Detection, Econometrics
• MLE: API Integration ,Feature Engineering, Model Lifecycle Management
• Analytics: Statistics, data distributions, summary/aggregation methods, operational metric development, ongoing OKR measurement
• Tools: Python, SQL, Tableau, Excel
• Collaboration: Confluence, Jira

More about you:

• You've been working in Machine Learning/ Data Science for 8+ years and have a BS degree in Statistics, Mathematics, Economics, Computer Science or other quantitative fields.
• Technical skills including best practices for operational Machine Learning Development and Serving
• Experience delivering value through data science, measuring impact, and right sizing solutions.
• Familiarity with Data Engineering and Software Engineering best practices
• You have experience building business improving Machine Learning Models and experience using data to guide efficiency in a business operations
• You have experience driving analytic projects, engaging with non-technical partners, and leading projects
• To keep pace with our growth you enjoy learning new things quickly. You can take an ambiguous assignment and deliver iterative value. You use multiple tools and methods to find trends and correlations by mining data, and light-weight tests to prioritize how to propel complicated problems.
• You are someone who likes to mentor less experienced analysts.
• You love driving strategy, making big changes, and influencing others. You have a history of driving measurable impact in close collaboration with operational colleagues.
• You combine curiosity with critical thinking and like asking "why" to unravel a seemingly complex problem and get to the cause.
• You're a senior 'pillar of the team' with business acuity, analytics expertise and the ability to up-skill those around you.
• When you encounter a problem you come up with multiple solutions, weigh the tradeoffs and efforts, identify the best path forward.

More About our team:

• We are a growing analytics and project delivery team located in multiple regions across the globe. We challenge each other always to improve our work and ask hard questions. We're direct and demand excellence, but there's laughter in every meeting because we thoroughly enjoy the work we do and the impact it has. We're constantly learning new things.