Interview DifficultymoderateRounds3 Rounds
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.
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This will be a call with non-technical questions. The objective is to check if your skills match the job role requirement. You will face some informal questions about your experiences and skills. They will emphasize on what led you to this point in life and why you want to work at Shopify as a Data Scientist. When asked, “Tell me about yourself,” add some important points or skills you carry to impress the interviewer to take you to the next round.
- Why do you want to join Shopify?
- Why do you think you will be a good fit for the role?
- What responsibilities do you expect to have from your job at Shopify?
- Describe a previous project of your choice, frame and solve a problem given a scenario.
The second round can either be a Pair Programming round or a Coding round. Candidates have reported experiencing either.
If you encounter a Pair Programming round, here’s what you can expect: You will be paired with a data scientist and will be given a dataset to work on and solve the given problem. The dataset problem could be a classification or regression problem. Here your analytical skills will be tested along with the approach you take to solve the given problem. A DS candidate reported being asked to work on Map Reduce as part of their Pair Programming exercise, for instance.
If you encounter a Coding Problem, here’s what you can expect: It will be focused on Object Oriented Programming in python. You will be asked to fix bugs and add more functionality to the code. There will be some questions related to Data Science concepts and questions related to Python and SQL.
- What is wrong with the given code and how would you fix it?
- What is your experience with OOP using python?
- Given a list of (date, duration) tuples, how would you filter by time period and calculate summary stats (average, rolling sum)?
- Program Conway’s game of life in Python.
- Basic operations on lists with some corner cases to think about.
- Write a recursive function in Python.
- Create an object class in Python to iterate over sequences.
Final round will usually be a combination of Technical Rounds and Behavioral rounds. You'll have a panel of interviewers (often senior data scientists) who will assess you across a range of skills and experiences.
You'll be tested across problem solving skills (often focusing on data analysis and visualization); you'll also be tested on product analytics and metrics; and finally - you'll face several behavioral questions.
A key part of the final round is what Shopify calls the "Life Story" round. This round is about your career journey such as what you have done till now. What are your strengths and weaknesses? Your interviewers will emphasize on what led you to this point in life and why you want to work at Shopify as a Data Scientist.
Some candidates have reported that they had this part of the conversation directly at the recruiter stage and didn't face this again during their onsite. In this context; we'd recommend being prepared for questions such as "What's your background and how do you think you reached this stage" up front, even for the recruiter rounds.
- How do you analyze if a product is successful?
- Explain how data manipulation works in pandas.
- How to create a simple string manipulation in Python?
- What is a median? How would you go about calculating a median from a dataset too large to store in memory?
When you are preparing for a Shopify Data Science interview - we’d recommend the following things to keep in mind:
- Make sure you practice and work on advanced SQL techniques. You should know NESTED JOINS, INNER/OUTER JOINS, PL/SQL etc - so this should give you an idea of what to expect.
- Think about how you’d apply statistical techniques to eCommerce businesses and their use cases.
- Work on implementing ETL pipelines and have some understanding of dimensional modeling.
- Brush up on basic math knowledge along with working on machine learning algorithms.
- Read about the business fundamentals behind e-commerce businesses.
- In Behavioral questions, your interviewer wants to understand your cultural fit for Shopify. One example of a question you may be asked is "What's your background and why do you want to work at Shopify." To make the most of this opportunity, take some time to reflect on your background and how it has prepared you for the data scientist role at Shopify, and also think about what specifically attracts you to the company and the work that they do.
- Be clear with your technical knowledge required to fit into the specific role you’re interviewing for at Shopify (most roles require you to index more heavily on specific aspects of the craft). Ensure you have practice in advance for the technical questions and rounds.
The interview process for a Data Scientist role at Shopify typically includes 3 primary rounds - a phone screening, technical interview, and the final interview rounds. During the phone screening, the interviewer will assess your qualifications, experience and alignment with the role. The technical interview will focus on your data science and programming abilities and is likely to include a coding test or problem-solving exercises. The final interview will typically include several rounds where you will be meeting with different people from the team (usually senior data scientists) and will include a mix of behavioral and technical questions, as well as a deep dive on a project or problem. Overall, the process is designed to give the interviewer a comprehensive understanding of your skills, background, and fit for the role, so be prepared to showcase your qualifications and experience.