Lead Data Scientist - SHOP (Europe)

Lead Data Scientist - SHOP (Europe)

This job is no longer open

About the role

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.

At Shop, Staff Data scientists use their expertise and drive to multiply the overall output of the data science team and deliver impactful solutions that power our Shop products. As a Staff Data scientist, you’ll help drive your team’s vision to its implementation. You will lead key initiatives that improve our understanding of customer behaviour, drive growth, and build data products that delight buyers and merchants. You’ll also be hands-on in our code and will contribute technically.

Your responsibilities:

  • Gather context to solve ambiguous problems that leads to long term impact

  • Partner closely with product, engineering and other business leaders to influence decisions with data

  • Apply different analytics and data science methods to inform improvements to our business

  • Identify, design and implement end-to-end focal data pipelines that scale and allow data & product to move fast

  • Identify and build actionable KPIs, production-quality dashboards, informative deep dives, and scalable data products

  • Advance best practices within data science and product teams

Qualifications

You will need to have:

  • Deep technical experience that inspires individual contributors, creativity and innovation. You can jump into the code on a deep level, but are also able to contribute to long term initiatives by mentoring your team,

  • Sound knowledge of applied statistics and quantitative modelling

  • A track record of communicating to technical and non-technical audiences 

  • Experience creating data product strategies, shipping data products and iterating after launch

  • Experience working closely with various levels of business stakeholders, potentially all the way up to c-suite

  • Curiosity about multiple problem domains and analytical approaches,

  • Strong sense of ownership and a growth mindset

It would be nice to have:

  • Extensive experience using Python including a strong grasp of object-oriented programming (OOP) fundamentals.

  • Good experience with SQL

  • Understanding of dimensional modelling and building ETL pipelines

  • Familiarity with GCP and Spark

  • Familiarity with Tableau, QlikView, Mode, or similar data visualization tools

  • Experience contributing to productionized machine learning models at scale

  • Domain experience in e-commerce, marketing, SaaS or other relevant areas

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

We know that looking for a new role can be both exciting and time-consuming, and we truly appreciate your effort.  We want to know what you're really interested in building and why you want to build it at Shop, so please give us as much detail on this as you'd like in the answers on the next page. 👍 📖

At Shop, we are committed to building and fostering an environment where our employees feel included, valued, and heard. Our belief is that a strong commitment to diversity and inclusion enables us to truly make commerce better for everyone. We strongly encourage applications from Indigenous peoples, racialized people, people with disabilities, people from gender and sexually diverse communities and/or people with intersectional identities. 

How we hire

At Shopify, we put a lot of care and time into who we hire. We believe that in order to build the best products, we need to build high impact teams. Our recruitment process centres around what we call the Life Story interview, a conversational-style interview where we get to learn more about you.

Learn more about our hiring process 

This job is no longer open
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