Shopify Data Scientist Interview Guide

Data science is a crucial part of Shopify’s mission to make commerce better for everyone. Data science at Shopify principally includes two types of work: building products directly backed by data (e.g. machine learning models), and listening to their voice to figure out what to build and how to build it. 

Shopify looks more for Data Scientists who have solved challenging problems than those familiar with specific tools or technologies. They are looking for talented data scientists to help them better understand their merchants and buyers.

Shopify hires Data Scientists across the company and there are different seniority levels depending on the scope and expected impact.They have Senior and Staff level roles and some openings for Data Science Managers. For instance, there was recently a role in Merchant Services - the goal being to give small businesses targeted advice that can help them better compete with larger ecommerce players. Given the scope and complexity of this undertaking, this was a Staff level role.

As a Data Scientist, you are expected to play a crucial role pushing forward product development across multiple domains. Data Scientists do this by informing high-level product strategy and execution, building a strong and broad operating picture allowing Shopify to move quickly, and/or improving underlying algorithms, heuristics and rules powering individual products - making the Shopify Data Scientist a sought-after role!

How to Apply for a Data Scientist Job at Shopify?

Take a look at Shopify’s website and visit their careers page. You'll find plenty of opportunities along with the Data Scientist role at Shopify, and you can easily apply to roles directly on the site. However, we highly recommend taking the referral route if you know someone in the company as it significantly increases your chances. Before you hit the apply button, make sure you read the job requirements thoroughly. Nothing's more frustrating than getting caught off guard during an interview. If you want to increase your chances even more, tailor your resume to align it with the qualifications and experiences listed in the job posting. It'll make you stand out from the rest. If you're not sure how to do that, Prepfully offers a resume review service, where actual recruiters will give you feedback on your resume.

Responsibilities of a Data Scientist at Shopify

The responsibilities of a data scientist at Shopify across roles can broadly be seen as-

• Actively seeking out and promoting projects that tackle vital issues.
• Utilizing Data Engineering frameworks (such as Starscream and Seamster) to gain insights.
• Being sufficiently familiar with BI tools such as Mode, PowerBI, and Tableau - to be able to visualize data in an effective way to drive insights.
• Collaborating with teams such as product, engineering, and other business leaders to make data-driven decisions.
• Utilizing analytical tools to identify opportunities and guide execution.
• Developing actionable KPIs, production-quality dashboards, informative deep dives, and scalable data products.
• Influencing leadership to drive more data-informed decisions across the organization.

Skills and Qualifications needed for Data Scientists at Shopify

Here are some skills and qualifications that will help you excel in your Data Science interviews at Shopify.

• It's beneficial to have at least 5+ years of experience in Data Science roles, which can help you stand out from other candidates. From what we’ve seen - candidates with less than 5 years of experience often struggle - even to get interview calls; let alone the interview loop.
• Brush up on your SQL skills and make sure you have a solid understanding of software engineering fundamentals.
• Being proficient in Object Oriented Programming will give you an edge in the interview process. This is because Data Scientists at Shopify are expected to be pretty much “full stack” in nature.
• Showcase your experience with applied statistics and your ability to solve quantitative problems.
• Be prepared to explain how you've turned analytical insights into clear recommendations, and demonstrate your ability to communicate effectively with technical and non-technical stakeholders.
• Highlight your understanding of dimensional modeling and the ability to scale ETL pipelines.
• Having experience launching productionized machine learning models at scale will give you an edge over the other candidates.
• A Domain experience in e-commerce, marketing or SaaS can help to tailor your approach in a specific industry.

As a part of the Shopify Data Scientist interview, the candidate will need to go through multiple interview rounds:

1. Recruiter call or Behavioural Round - The first round is to have a quick discussion about your work experiences and the roles you’ve had in the past company.

2. Pair Programming or Coding round - The second round is to test your data science concepts and SQL and Python-related concepts. This is to test your analytical skills and to see the approach you take to solve the given problem.

3. The final round of Shopify Data Scientist interviews will usually be a combination of technical rounds and behavioral rounds. You will have a panel of interviewers (often senior data scientists) who will assess you across a range of skills and experiences. The skills you will be likely tested on are: product analytics, metric analysis and behavioral/leadership skills.