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.
Data Science & Engineering
The Data Science & Engineering (DSE) team consists of 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
The Role - Data Products Team
We are building a multi-product company with a growing offering including Invest, Cash, Crypto, Trade and Tax products.
As a Data Scientist on the Data Products team, you will play a pivotal role in our mission to discover and deploy sustainable machine learning solutions to opportunities that exist across the organization. As such, you will work closely with the area owners along with a cross functional team consisting of full stack developers, product managers and operation specialists to unlock delightful product experiences and improve our operational efficiency.
We are looking for a senior data scientist with strong foundations in Python programming, fundamental understanding of machine learning algorithms, and preferably experience developing and deploying sustainable machine learning products into production.
Some projects include:
Developing a discovery feature to connect relevant content to clients looking to improve awareness and pertinent information for decision making (NLP, recommendation engine).
Enriching and later leveraging internal social graph to power referral, fraud and growth initiatives (Graph embeddings, ranking)
Launching long-term projects involving OCR to streamline identity verification and manual operational actions
Improving existing Machine Learning models for enhancing the client onboarding experience
In this role, you will:
Love data to make better decisions
Build stakeholder relationships to identify high impact opportunities which can be solved using machine learning
Believe that simple is better, Occam's razor is your friend
Take ownership and ship it
You release incrementally and iteratively
Get the best out of the team by leveraging their diverse educational backgrounds
Teach and learn from their teammates. We value making others successful
We are looking for people who have:
Excellent Python & SQL skills. Candidate should be an expert with OOP and complex data manipulation
Strong understanding of fundamental machine-learning algorithms - how they work, when to use them, strengths, limitations, implementations: linear / logistic model, SVM, KNN, tree-based models, k-means, word2vec, graph embeddings, etc.
Demonstrate knowledge in fundamentals of deep learning: initialization, backpropagation & gradient flow, optimization methods, etc. as well as familiarity with state-of-the-art architectures in DL domains
Strong understanding of statistics: both frequentist and Bayesian approaches
Excellent communicator
At least 3 years of first hand experience working with popular Python libraries such as pandas, scikit-learn, numpy, matplotlib
Expertise with deep learning frameworks like TensorFlow or PyTorch. It would be great if you have experience working with model hubs like tfhub or huggingface as well
Bonus points for hands-on experience with MLFlow, Apache Airflow, and a BI tool like Periscope, Mode Analytics or Tableau. Web development skills also appreciated
Bonus points for personal projects / research demonstrating candidate’s skills and domain knowledge