Senior Data Scientist (EMEA - Remote)

Shopify is now permanently remote and working towards a future that is digital by design. While UK is one of our hubs, this role is open to candidates in European time zones. Learn more about what this can mean for you.

At Shopify, we build products that help entrepreneurs around the world start and grow their business. We’re the world’s fastest growing commerce platform with millions of merchants in more than 175 different countries, with solutions from point-of-sale and online commerce to financial, shipping logistics and marketing.

Data is a crucial part of Shopify’s mission to make commerce better for everyone. We organize and interpret petabytes of data to provide solutions for our merchants and stakeholders across the organization. From pipelines and schema design to machine learning products and decision support, data science at Shopify is a diverse role with many opportunities to positively impact our success.

Our data scientists focus on pushing products and the business forward, with a focus on solving important problems rather than specific tools. We are looking for talented full-stack data scientists to help us better understand our merchants and buyers so we can help them on their journey.

Please note, this team is based in EMEA/Europe, and we are specifically looking for people to join us in these regions only.

Your responsibilities:

• Proactively identify and champion projects that solve complex problems across multiple domains.
• Partner closely with product, engineering and other business leaders to influence product and program decisions with data.
• Apply specialized skills and fundamental data science methods (e.g. regression, survival analysis, segmentation, experimentation, and machine learning when needed) to inform improvements to our business.
• Design and implement end-to-end data pipelines: work closely with stakeholders to build instrumentation and define dimensional models, tables or schemas that support business processes.
• Build actionable KPIs, production-quality dashboards, informative deep dives, and scalable data products.
• Influence leadership to drive more data-informed decisions.
• Define and advance best practices within data science and product teams.

You will need to have:

• Extensive experience with Python and software engineering fundamentals.
• Experience with applied statistics and quantitative modeling (e.g. regression, survival analysis, segmentation, experimentation, and machine learning when needed).
• Demonstrated ability to translate analytical insights into clear recommendations and effectively communicate them to technical and non-technical stakeholders.
• Curiosity about the problem domain and an analytical approach.
• Strong sense of ownership and growth mindset.

You should have one or more of:

• Deep understanding of advanced SQL techniques
• Expertise with statistical techniques and their applications in business
• Strong data storytelling and strategic thinking
• Deep understanding of dimensional modelling and scaling ETL pipelines
• Experience launching productionized machine learning models at scale
• Extensive domain experience in e-commerce, marketing or SaaS

We know that looking for a new role can be both exciting and time-consuming, and we truly appreciate your effort. Dan is an actual real live person and is looking forward to learning more about you and your interest in joining our team.

#LI-REMOTE

Our belief is that a strong commitment to diversity & inclusion enables us to truly make commerce better for everyone. We encourage applications from Indigenous peoples, racialized people, people with disabilities, people from gender and sexually diverse communities, and/or people with intersectional identities. Please take a look at our Sustainability Reports to learn more about Shopify’s commitments to our communities, and our planet.

At Shopify, we understand that experience comes in many forms. We’re dedicated to adding new perspectives to the team - so if your experience is this close to what we’re looking for, please consider applying.