Senior Data Scientist

Company Description
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 millions of merchants in more than 175 different countries, with solutions from point-of-sale and online commerce to financial, shipping logistics and marketing.

Shopify is now permanently remote and working towards a future that is digital by default**. **Learn more** **about what this can mean for you.

**Job Description**:
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 is to join the APAC Revenue Data team, which is the data science team supporting the APAC Revenue org. Revenue is Shopify’s go-to-market org, which encompasses functions such as marketing, sales, partnerships, merchant success and support. The APAC data science team therefore works with these business stakeholders to get the Shopify product in the hands of merchants in APAC, and ensure that they grow and succeed on the platform. In addition we collaborate with and learn from our data science peers spread across the other regions and crafts within the company.

This role is to be based within Asia-Pacific (APAC) preferably in Singapore, India or Australia.

**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- 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**:

- 5+ years of experience as a Data scientist. Domain experience in e-commerce, marketing or SaaS would be a plus.
- Bachelor’s or Master’s degree in Information Technology, Mathematics, Computer Science or equivalent is preferred
- Extensive experience with Python or Pyspark and software engineering fundamentals
- Deep understanding of advanced SQL techniques, dimensional modeling and scaling ETL pipelines
- 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; Masterful data storytelling and strategic thinking
- Strong sense of ownership and growth mindset; self-motivated and able to thrive in a remote environment
- Excellent communication skills; proficiency in English is a must

Additional Information

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.
**Interested, but not ready to apply?**- 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._