Atlassian is looking for a senior Data Scientist to join our Experimentation Data Science team. The Experimentation Data Science team partners with the experimentation engineering team to help unlock Atlassian's experimentation capabilities. We help teams execute experiment successfully by delivering training, tools, and analyses to go from idea to decision as quickly as possible. This is a unique opportunity to work in a collaborative environment to create a culture of experimentation and tackle challenging problems as we scale.
Compensation
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. To support this goal, the baseline of our range is higher than that of the typical market range, but in turn we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience. In the United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
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Zone A: $175,100 - $233,400
Zone B: $157,600 - $210,100
Zone C: $145,300 - $193,800
This role may also be eligible for benefits, bonuses, commissions, and equity.
Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
As an Experimentation Data Scientist, you will drive the experimentation execution practices and analyses, collaborating with business, engineering, and data science teams, to enable trustworthy decisions at scale. Additionally, you will lead the organization to develop and adopt novel ways (sprt, stratified random sampling, etc.,) to increase the speed of the experimentation lifecycle.
On the first day, we'll expect you to have
- Masters in a quantitative subject (Statistics, Mathematics, Computer Science, Operations Research, or relevant work experience)
- 3+ years of related industry experience in the data science and experimentation domain
- Experience building and scaling experimentation practices, statistical methods, and tools in a large scale organization
- Experience with causal inference, multi-arm bandits. reinforcement learning, synthetic data and experimentation, non-parametric methods
- Expertise in SQL, familiarity with Python, knowledge of Spark and cloud data environments (e.g. AWS, Databricks)
- Ability to communicate and explain data science and experimentation concepts to diverse audiences by crafting compelling stories that drive behavior change
- Focus on business practicality and the 80/20 rule; very high bar for output quality, but recognize the business benefit of "having something now" vs "perfection sometime in the future"
- Agile development mindset, appreciating the benefit of constant iteration and improvement
It's great, but not required, if you have
- Experience working in a consumer or B2C space for a SaaS product provider, or the enterprise/B2B space
- Familiarity working with Growth, Product, and engineering teams
- Excelling in solving ambiguous and complex problems, being able to navigate through uncertain situations, breaking down complex challenges into manageable components and developing innovative solutions