Wealthsimple is on a mission to help everyone achieve financial freedom, no matter who they are or how much they have. Using smart technology, Wealthsimple takes financial services that are often confusing, opaque and expensive and makes them simple, transparent, and low-cost. We're the company behind some of Canada's leading digital financial products, and are growing faster than ever.

Our team is reimagining what it means to manage your money. Smart, high-performing team members will challenge you to learn and grow every day. We value great work and great ideas — not ego. We're looking for talented people who love a fast-paced environment, and want to ship often and make an impact with groundbreaking ideas.

We’re a remote-first team and output is more important than face time, so where you choose to work is up to you — as long as you have internet access, you can work from anywhere in Canada. 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.

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. Wealthsimple provides an accessible candidate experience. If you need any accommodations or adjustments throughout the interview process and beyond, please let us know.

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

We are looking for a Data Science Manager who has strong foundations in data modelling, statistics and product analytics to work on Wealthsimple Cash. Wealthsimple Cash is a mobile-first peer-to-peer payments product that allows anyone to instantly send money to friends and family for free. But that’s just the beginning. We’re on a mission to create the most human everyday banking platform in Canada: a simple, beautiful, and no-cost option that makes sending, saving, and spending money fast, fun, and rewarding.

As the Data Science Manager of Cash, you will manage and grow a team of Data Scientists and collaborate with product managers, engineers, and designers to unlock unique growth opportunities for the Cash product. This includes, but is not limited to, finding innovate ways to utilize peer-to-peer network data, design experiments to test hypotheses and perform statistical analysis to inform business and product decisions. The perfect candidate will be scrappy, focused on results and have a demonstrated track record of driving data-informed decisions.

Own the data science strategy for metrics and data models for the Wealthsimple Cash team

Build and maintain new data models that are accurate and reliable

Design, define, and implement metrics and dimensions to enable analysis and predictive modelling

Partner with Product and Engineering teams to solve impactful problems

Think outside the box and design experiments to test hypotheses

Build/maintain reports, dashboards, and metrics to monitor the performance of our products

Help build and lead a great data science team to deliver world-class products

Get the best out of the team by leveraging their diverse educational backgrounds

Teach and learn from their teammates. We value making others successful

Excellent Python & SQL skills

Strong understanding of statistics: both frequentist and Bayesian approaches

Experience with applied statistics or experimentation (i.e. A/B testing) in an industry setting

Strong understanding of fundamental machine-learning algorithms: regression and decision trees

First hand experience working with popular Python libraries such as Pandas, scikt-learn, numpy and Jupyter

Excellent communicator who is able to present results and analysis to senior leadership

Experience in managing team members in a formal or informal capacity

It’s a bonus if you have hands-on experience with Apache Airflow, and a BI tool like Periscope, Mode Analytics or Tableau