Senior Data Scientist (APAC - Remote)

Job post summary
Location Asia
Team Data Science and Engineering

About the role

At Shopify, we build products that help entrepreneurs around the world start and grow their businesses. We’re the world’s fastest growing commerce platform with over 1 million 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 organise and interpret petabytes of data to provide solutions for our merchants and stakeholders across the organisation. 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 data scientists to help us better understand our merchants and buyers so we can help them on their journey.

This role can be based anywhere in Singapore, Japan, Australia or New Zealand.

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 specialised 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

Qualifications

  • Native-level English
  • 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
  • Masterful data storytelling and strategic thinking
  • Deep understanding of dimensional modeling and scaling ETL pipelines
  • Experience launching productionized machine learning models at scale
  • Extensive domain experience in e-commerce, marketing or SaaS

We know that applying to a new role takes a lot of work and we truly value your time. We’re looking forward to reading your application! 

At Shopify, 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 people, racialized people, people with disabilities, people from gender and sexually diverse communities and/or people with intersectional identities. Please take a look at our 2019 Sustainability Report to learn more about Shopify's commitments.

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 
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