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Atlassian

Senior Data Scientist

Atlassian, San Francisco, California, United States, 94199


Overview:

Working at Atlassian

This section is standardized across all Atlassian roles. Atlassians can choose where they work whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Interviews and onboarding are conducted virtually, a part of being a distributed-first company. This is a remote position. To help our teams work together effectively, this role requires you to be located in the Pacific / Mountain timezones. Your future team

You will be part of a world-class Data Science team that leverages data to drive insights about our products and customers. The Data Science team partners with Product Managers/Researchers/Data Engineers/Marketers/Privacy and Executive teams to drive and influence. They use a variety of analysis and data-science techniques to understand how Atlassians customers engage with our products and communications and, in doing so, identify, design, and measure the success of product investments. 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: 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. Responsibilities: In this role, you will:

Collaborate on a variety of product and business problems with a diverse set of cross-functional partners and become a trusted strategic partner through the structure and clarity of your work.

Apply technical expertise with quantitative analysis, experimentation, and the presentation of data to develop strategies for our business and help solve the business's biggest challenges.

Focus on developing hypotheses through analytical approaches, different methodologies, frameworks, and technical approaches to test them.

Define, understand, and test opportunities to improve the products and business and influence roadmaps through insights and recommendations.

Partner with cross-functional teams to inform, influence, and execute strategy decisions

Identify and measure the success of product efforts through forecasting and monitoring of key product metrics to understand trends.

You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Atlassian.

Qualifications: Minimum Qualifications / Your background:

5+ Years of Experience in Data Science or related fields

Proficiency in SQL AND another data manipulation programming language (e.g Python, R)

Expertise at telling stories with data and familiarity with at least one visualization tool (e.g. Tableau, R-Shiny, Microstrategy, SAP Business Objects, Looker, etc.)

Experience in applying statistical concepts (e.g. regressions, A/B tests, clustering, probability) to business problems

Experience driving projects or programs which have had proven impact on business strategy and performance through your analytics skills

Ability to craft analysis into well-written and persuasive content

Desirable Qualifications

7+ Years of Experience in Data Science or related fields OR 5+ Years of experience in Data Science along with a post-graduate degree or equivalent in a related field

An understanding of the SaaS business model and key metrics