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Principal Data Scientist

Broken Build·$171,063 – $269,075

Primary stack

Machine Learning

Nice to have's

MentoringCross-functional CollaborationFeature EngineeringModel MonitoringResponsible AI/ML

Job description

About the Position

As a Principal Data Scientist on the Global Experiences Data Science team, you'll sit at the intersection of cutting-edge analytics and Atlassian's most customer-facing products. Reporting to the Manager of Global Experiences Data Science, you'll bring deep technical expertise to complex, ambiguous problems - shaping how millions of users experience Atlassian's suite of products.

This is a high-impact, high-visibility role where you'll lead the full data science lifecycle: from defining the right questions and building robust models to influencing product strategy and communicating insights to senior leaders. You'll be a force multiplier for the team - elevating the craft of data science while partnering closely with Product, Engineering, and Design to drive meaningful outcomes at scale.

Responsibilities

  • Define and drive the data science strategy for your product area, translating ambiguous business problems into rigorous analytical frameworks and measurable outcomes
  • Lead end-to-end development of ML models and statistical analyses - from problem framing and data acquisition through experimentation, deployment, and ongoing evaluation
  • Partner with Product, Engineering, and Design to embed data-driven decision-making into the product development lifecycle
  • Own experimentation infrastructure and methodology for your domain, including A/B test design, power analysis, and interpretation of results at scale
  • Identify high-impact opportunities through exploratory analysis, surfacing insights that influence roadmap prioritization and business strategy
  • Serve as the technical authority for data science within your team - setting standards for modeling approaches, code quality, and analytical rigor
  • Mentor and develop junior and mid-level data scientists; contribute to hiring, onboarding, and capability-building across the broader DS organization
  • Communicate findings and recommendations clearly to senior stakeholders and executives, translating complex analyses into actionable narratives
  • Collaborate cross-functionally to define metrics frameworks, north star metrics, and guardrail metrics for product and business health
  • Drive adoption of best practices in feature engineering, model monitoring, and responsible AI/ML across teams

Requirements

  • Core Skills:
    • Data Science
    • Machine Learning
    • Statistical Analysis
    • Product Strategy
  • Secondary Skills:
    • Mentoring
    • Cross-functional Collaboration
    • Feature Engineering
    • Model Monitoring
    • Responsible AI/ML

We Offer

  • Compensation:
    • Base pay ranges from $171,063 - $269,075 per year, depending on the geographic pay zone.
  • Benefits & Perks:

About the Company

At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.

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 provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.

To learn more about our culture and hiring process, visit go.atlassian.com/crh.

In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.

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