Data Scientist Credit at Wealthsimple

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 facetime, 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.

About the team:
The Credit Models & Data team is new at Wealthsimple and we want to build a team of exceptional data professionals with diverse educational backgrounds. The team is responsible for delivering predictive analytics to support data-driven management of credit risk. These products will help support a new suite of retail lending products at Wealthsimple. The team is staffed with seasoned lending experts and supported by product managers, MLOps engineers, credit strategy experts, and data engineers. This team is a great place to learn about credit risk machine learning and a great place to see your models deliver a big impact to the business. 

About the role:
As a Data Scientist on the Credit Models & Data team, you will play a pivotal role in quantifying risk and credit worthiness of clients. You should have strong programming skills in Python and SQL, extensive experience in machine learning and product data science, confidence articulating your results, and preferably domain knowledge in retail lending. You will work closely with the Product, Operations, and Finance teams, as a member of this highly cross-functional team consisting of full stack developers, product managers, and analysts to find new opportunities to manage and control risk. Your work will be foundational in Wealthsimple’s goal to be the primary financial service provider to millions of Canadians.

Some projects include:
- Building and deploying real-time machine learning models for credit risk prediction across products
- Developing frameworks to optimize various credit offerings
- Understanding product financials and resilience to economic factors
- Defining processes to rapidly update models with new innovative data sources
- Experimental design for product optimization and data collection

In this role, you will have the opportunity to:
- Use data to make better decision, take ownership and ship it
- 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

Skills we are looking for:
- Strong programming skills: 
	Python and SQL
- Data manipulation, feature engineering, model tuning and validation, familiarity with consumer financial data
- Strong understanding of statistics: distributions, experimental design, information, metrics, etc.
- Strong understanding of common machine-learning algorithms: boosting, regression, decision trees, clustering, and neural networks
- First hand experience working with popular ML libraries for 5+ years
- The curiosity to explore data and the tenacity to get it right
- Excellent communicator who is able to tailor a narrative to their audience


Nice to have: 
- MLOps experience in AWS, experience in credit risk (adjudication, AIRB) or market risk (VaR, ES), experience in graph data science (e.g. graph databases / GNNs), Transfer Learning, Reinforcement Learning, Apache Airflow, Kafka, Spark, Flink