Company Description: About ShopifyOpportunity is not evenly distributed. Shopify puts independence within reach for anyone with a dream to start a business. Since 2006, we’ve grown to over 10,000 employees and generated over $500 billion in sales for millions of merchants in 175 countries. Every 28 seconds, an entrepreneur on Shopify makes their first sale.This is life-defining work that directly impacts people’s lives as much as it transforms your own. This is putting the power of the few in the hands of the many, is a future with more voices rather than fewer, and is creating more choices instead of an elite option.About you

Moving at our pace brings a lot of change, complexity, and ambiguity—and a little bit of chaos. Shopifolk thrive on that and are comfortable being uncomfortable. That means Shopify is not the right place for everyone.Before you apply, consider if you can:* Care deeply about what you do and about making commerce better for everyone

Excel by seeking professional and personal hypergrowth
Keep up with an unrelenting pace (the week, not the quarter)
Be resilient and resourceful in face of ambiguity and thrive on (rather than endure) change
Bring critical thought and opinion — and embrace differences and disagreement to get shit done and move forward
Work digital-first for your daily work

Job Description: The Revenue Acceleration Data Science team drives Shopify’s go-to-market machine with data and insights. The team’s mission is to increase Shopify’s revenue and profitability and the team's impact is grounded in experiment-based findings.As a Staff Data Scientist, you will use elements of analytics, machine learning, experimentation, and build data products to increase Shopify’s revenue and profitability.

Qualifications: You will need to have:* Extensive experience using Python including a strong grasp of object oriented programming (OOP) fundamentals

Deep understanding of advanced SQL techniques
Experience designing and running experiments (e.g. A/B test)
Experience building data pipelines and driving ETL design decisions
Experience creating data product strategies, shipping data products, iterating after launch, and trying again
Strong ability to prioritize and communicate to technical and non-technical audiences alike
Experience working with commercial organizations (e.g. Sales, Marketing, Account Management, Support, etc…)
Experience building machine learning models (e.g. propensity models, recommendation system, etc…)
Experience setting up experiments in commercial organizations
Previous experience working at a large technology company We hire people, not resumes. If you think you’re right for the role, apply now.

Additional Information: All your information will be kept confidential according to EEO guidelines.

Senior Data Scientist - Revenue Acceleration, Recommendation (Remote, Americas)