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Work setup in the employer’s posting: RemoteFrom the employer’s posting
Employment type in the employer’s posting: FullTimeFrom the employer’s posting
Analyze AI-assisted development, CI/CD, testing and deployment data to guide engineering investments
Build data products and measurement frameworks for developer velocity, quality and infrastructure cost
Apply causal inference, experimentation and metric design to find what accelerates or blocks development
Translate technical systems into priorities and data-backed recommendations for engineering leaders
Coach and mentor other data scientists on broad, ambiguous projects
analyzing AI-assisted development, CI/CD, local developer environments, testing, deployment workflows
Lead a small team of data scientists working on building data products and measurement frameworks
Apply statistical models, causal inference, segmentation techniques, experimental methods, and rigorous metric design
Partner with engineering leaders, product managers, data scientists, and finance partners to translate complex technical systems into clear priorities
coaching and mentoring other data scientists
Proficiency in programming languages such as Python, and experience with data visualization tools
Experience in statistical analysis, data modelling, experimentation, causal inference, or machine learning at scale
Experience translating complex data into clear insights that inform business, product, and engineering decisions
Experience leading, coaching, or mentoring data scientists through broad, ambiguous work
Actively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 6
Early. Similar jobs usually come down between day 7 and day 55.
From 9,988 similar postings that came down. Coming down is not always a hire.
20 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Fluency in SQL - Proficiency in programming languages such as Python, and experience with data visualization tools - Experience in statistical analysis, data modelling, experimentation, causal inference, or machine learning at scale
Qualifications - Fluency in SQL - Proficiency in programming languages such as Python, and experience with data visualization tools
Complete your application on www.shopify.com. The employer’s form will show what is required.
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We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Are you ready to decode how great software gets built through the power of data? As a Staff Data Scientist at Shopify working on developer productivity, you'll lead the data science strategy for this space as a player/coach: leading a small team of data scientists, going deep on ambiguous problems yourself, and applying different methodologies to solve distinct challenges - from metric design and instrumentation to causal inference, cost attribution, experimentation, and executive storytelling. Developer Productivity experience is a plus, but not a requirement; we're looking for someone who has created clarity in complex systems and is excited to go deep on how engineering work happens.
You will work with rich signals from the systems that power Shopify’s engineering organizations - analyzing AI-assisted development, CI/CD, local developer environments, testing, deployment workflows, and the infrastructure that helps builders turn ideas into merchant impact. You'll deeply understand how engineers build at Shopify, tell the story of what helps or slows them down, and figure out how to make measurable, compounding improvements.
This is data science at the center of how Shopify builds. Every analysis you run, every measurement framework you shape, and every data product you build can influence how engineers spend their time and how quickly Shopify learns, ships, and improves commerce for merchants. You'll answer complex questions and collaborate with cross-functional partners to build data-informed solutions that improve developer velocity from local development to production. Through insights that guide our Developer Productivity investments, you'll help determine what we build, what we scale, and where we invest next.
Develop insights through advanced analytics and data exploration across developer workflows, infrastructure systems, AI-assisted development, CI/CD, testing, and deployment to inform engineering strategy and investment decisions
Lead a small team of data scientists working on building data products and measurement frameworks that improve how Shopify understands developer velocity, engineering quality, infrastructure cost, reliability, and developer experience
Partner with engineering leaders, product managers, data scientists, and finance partners to translate complex technical systems into clear priorities and measurable decisions
Apply statistical models, causal inference, segmentation techniques, experimental methods, and rigorous metric design to understand what accelerates development and what creates friction
Influence decision-making by providing clear, data-backed recommendations that shape where Shopify invests in AI, developer tooling, and infrastructure
Lead high-impact projects through complex, ambiguous problems while coaching and mentoring other data scientists
Apply rigorous analytics techniques, including AI/ML tools where applicable
Fluency in SQL
Proficiency in programming languages such as Python, and experience with data visualization tools
Experience in statistical analysis, data modelling, experimentation, causal inference, or machine learning at scale
Experience translating complex data into clear insights that inform business, product, and engineering decisions
Lead efforts to solve complex product, technical, and business problems with data in ambiguous, fast-moving environments
Comfort working quickly and iteratively in ambiguous, high-impact environments
Experience leading, coaching, or mentoring data scientists through broad, ambiguous work
Ready to transform data into groundbreaking solutions for how Shopify builds? Join the team that's making commerce better for everyone.
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