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Senior Data Scientist, Investing Data Science

Your career is an investment that grows over time!


Wealthsimple is on a mission to help everyone achieve financial freedom by reimagining what it means to manage your money. Using smart technology, we take financial services that are often confusing, opaque and expensive and make them transparent and low-cost for everyone. We’re the largest fintech company in Canada, with over 4 million users who trust us with more than $50 billion in assets.


Our teams ship often and make an impact with groundbreaking ideas. We're looking for talented people who keep it simple and value collaboration and humility as we continue to create inclusive and high-performing teams where people can be inspired to do their best work.


About the team:

The Data Science & Engineering (DSE) team consists of analytics engineers, data scientists, and software engineers with diverse educational backgrounds such as math, operations research, economics, computer science, engineering and business. The team is responsible for enabling data-driven decision making and building data products at Wealthsimple.


We achieve these goals by:

-Building a high quality and scalable state-of-the-art data warehouse that powers all decision making

-Leveraging machine learning and algorithms to help Wealthsimple build smarter financial products

-Using decision science to understand the cause and effect of our business decisions


About the role:

At Wealthsimple, our Investing teams are the driving force behind Self Directed Investing and Managed Invest products. We are hiring for an experienced data scientist to join our Investing DSE team. This individual will work on some of the highest priority initiatives at Wealthsimple, ensuring that our product strategy is well grounded in data analytics.


Some of your projects may include, but are not limited to:
  • Analyze user behaviour to understand how clients interact with the product
  • Develop and implement experiments to evaluate new features and product changes
  • Apply causal inference methods in non-experimental settings
  • Use machine learning algorithms to segment users and personalize product experiences
  • Develop and maintain core data models and pipelines to ensure data quality and accessibility


In this role, you will have the opportunity to:
  • Partner with our Product, Product Marketing, and Engineering teams to support work across some of Wealthsimple's highest priority efforts
  • Build robust, efficient, and integrated data models in cloud data warehouses that will be used as the source of truth for analytics across the Investing product organization
  • Apply statistical techniques and build machine learning models to solve real life product problems and to inform product decisions and strategies
  • Apply software engineering best practices like version control and continuous integration to the analytics code base; ensure data models are well tested, documented and maintained
  • Translate business requirements into data models and analysis that will help stakeholders answer key business questions and inform strategic decisions
  • Continuously look for the simplest, most effective way to approach challenges; Occam's razor is your friend
  • Take ownership and ship it
  • Work where you are (while our Canadian offices are located in Toronto, we are a remote-first workforce and you can join from anywhere in Canada)


Skills we are looking for:
  • Strong business acumen and product sense
  • Excellent Python and SQL skills, first hand experience working with popular Python libraries such as Pandas, scikit-learn, numpy and Jupyter
  • Strong understanding of statistics: both frequentist and Bayesian approaches
  • Strong understanding of fundamental machine-learning algorithms: regression and decision trees


We are looking for someone who:
  • Is able to articulate their stance in a manner that effectively collaborates with different stakeholders
  • Adjusts quickly to changing priorities and effectively manages complexity and change
  • Has exceptional communication skills and is able to communicate effectively with both technical and non-technical teams
  • Is eager to teach and learn from your team. We value making each other successful
  • Is a lifelong learner. You're constantly seeking and welcoming feedback to continue improving yourself and your craft


Why Wealthsimple?

🤑 Competitive salary with top-tier health benefits and life insurance

📈 Retirement savings matching plan using Wealthsimple Work

🌴 20 vacation days per year and unlimited sick and mental health days

📚 Up to $1,500 per year towards wellness and professional development budgets respectively 

🛫 90 days away program: Employees can work internationally in eligible countries for up to 90 days per calendar year 

🌎 A wide variety of peer and company-led Employee Resource Groups (ie. Rainbow, Women of Wealthsimple, Black @ WS)

💖 Company-wide wellness days off scheduled throughout the year


We’re a remote-first team, with over 1,000 employees coast to coast in North America. Be a part of our Canadian success story and help shape the financial future of millions — join us!


Read our Culture Manual and learn more about how we work.


DEI Statement

At Wealthsimple, we are building products for a diverse world and we need a diverse team to do that successfully. We strongly encourage applications from everyone regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability status. 


Accessibility Statement

Wealthsimple provides an accessible candidate experience. If you need any accommodations or adjustments throughout the interview process and beyond, please let us know, and we will work with you to provide the necessary support and make reasonable accommodations to facilitate your participation. We are continuously working to improve our accessibility practices and welcome any feedback or suggestions on how we can better accommodate candidates with accessibility needs.

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CEO of Wealthsimple
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What You Should Know About Senior Data Scientist, Investing Data Science, Wealthsimple

Your career is an investment that grows over time! Wealthsimple is on a mission to help everyone achieve financial freedom by reimagining what it means to manage your money. We're currently seeking a Senior Data Scientist for our Investing Data Science team, and it couldn't be a more exciting time to join us! In this role, you will be diving into high-priority initiatives, analyzing user behavior, and developing experiments to evaluate new financial product features. You'll apply advanced machine learning algorithms to personalize user experiences, ensuring our product strategy is firmly grounded in data analytics. With a team filled with talented analytics engineers and data scientists, collaboration is key. You will partner with product, marketing, and engineering teams, building robust data models that serve as the backbone of our analytics efforts. Your work will harness statistics and innovative data techniques to solve real-world problems and enhance our offerings. If you're eager to take ownership, be part of a remote-first culture, and help us shape the financial future of millions, we’d love to hear from you. Join us at Wealthsimple as we continue to revolutionize the financial services landscape in Canada!

Frequently Asked Questions (FAQs) for Senior Data Scientist, Investing Data Science Role at Wealthsimple
What are the responsibilities of a Senior Data Scientist at Wealthsimple?

As a Senior Data Scientist at Wealthsimple, your responsibilities will cover analyzing user behavior, developing experiments for product evaluation, applying causal inference methods, employing machine learning for user segmentation, and maintaining data models to ensure quality and easy access. You’ll play a pivotal role in translating business needs into actionable insights that drive our investment products forward.

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What skills are required for the Senior Data Scientist position at Wealthsimple?

Candidates for the Senior Data Scientist position at Wealthsimple should possess strong business acumen and product sense. Essential technical skills include proficiency in Python and SQL, experience with libraries like Pandas and scikit-learn, and solid statistical knowledge encompassing both frequentist and Bayesian approaches. A robust understanding of machine learning algorithms is also crucial for success in this role.

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What can I expect from the work culture at Wealthsimple as a Senior Data Scientist?

Working as a Senior Data Scientist at Wealthsimple offers a collaborative, remote-first culture where innovation thrives. With a focus on humility and mutual support, Wealthsimple encourages continuous learning and development. You’ll find a diverse team of professionals dedicated to making impactful contributions to financial technology while maintaining a balanced lifestyle.

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How does Wealthsimple support career growth for Senior Data Scientists?

Wealthsimple values personal and professional growth, providing various resources for learning and development. As a Senior Data Scientist, you'll have access to up to $1,500 annually for professional development, as well as opportunities to collaborate across teams. Regular feedback and mentorship from colleagues further enhance your career progression within the company.

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What is the remote work policy for the Senior Data Scientist role at Wealthsimple?

Wealthsimple is proud to be a remote-first organization, allowing Senior Data Scientists to work from anywhere in Canada. While our offices are based in Toronto, the flexibility of remote work supports a healthy work-life balance while contributing to a diverse and inclusive company culture.

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Common Interview Questions for Senior Data Scientist, Investing Data Science
Can you explain your experience with machine learning algorithms as a Senior Data Scientist?

When answering this question, provide specific examples of projects where you have implemented machine-learning algorithms. Highlight the algorithms used, the data challenges faced, and the impact your contributions had on product outcomes.

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How do you approach data quality in your analysis?

Discuss your process for ensuring data quality, such as validating data sources, cleaning datasets, and building robust data pipelines. Emphasize how you prioritize data integrity to inform business decisions effectively.

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What techniques do you use for user segmentation?

Here, describe various techniques you’ve employed for user segmentation, such as clustering algorithms or decision trees. Use examples from your past work to demonstrate successful applications.

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Describe a time you faced a complex data challenge. How did you handle it?

Use the STAR method to clearly outline the Situation, Task, Action, and Result. Sharing a specific story that showcases your problem-solving skills and analytical thinking will reflect your capability as a Senior Data Scientist.

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How do you ensure collaboration with product and engineering teams?

Talk about your communication strategies, tools you use, and how you foster relationships with cross-functional teams. Providing examples of successful collaborations can highlight your team-oriented approach.

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What statistical methods do you find most effective in data analysis?

List the statistical methods you frequently utilize, explaining why they are effective in your analysis. Discuss both frequentist and Bayesian approaches while sharing how they have informed product strategies.

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How do you handle feedback and criticism from your peers?

Discuss your mindset toward feedback, emphasizing openness and continuous learning. Share examples of how you’ve incorporated feedback into your projects to improve processes and outcomes.

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What data visualization tools do you prefer and why?

Mention your favorite data visualization tools, such as Tableau or Matplotlib, discussing their functionalities and how they enhance data storytelling in your analyses. Providing examples of impactful visualizations you’ve created will strengthen your answer.

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Can you provide an example of how you’ve used A/B testing in your work?

Share a specific A/B testing example, detailing the hypothesis, testing process, and results. Highlight how this experience enhanced product features or user engagement in a measurable way.

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What would you prioritize when working on multiple data projects?

Illustrate your prioritization process, such as assessing project impact, deadlines, and stakeholder needs. Discuss strategies you implement to manage time effectively while ensuring quality outcomes.

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Full-time, remote
DATE POSTED
April 3, 2025

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