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 Credit Models & Data team is new at Wealthsimple and we want to build a team of exceptional data professionals with diverse backgrounds. The team is responsible for delivering predictive analytics to support data-driven management of credit risk. These data products will help support a new suite of retail lending products at Wealthsimple. The team is staffed with seasoned data experts and well supported by product managers, software engineers, and credit strategy experts.

We are hiring for an Analytics Engineer in the Credit Models & Data team to work with data scientists, credit analysts and product managers. You will be responsible for building robust, efficient and integrated data models that enable our credit analytics and machine learning. These data models will serve as the foundation of our credit strategy, allowing the team to monitor and detect credit trends, build machine learning models, and launch new credit products. As an expert in credit data, you will be leading the charge against machine learning feature engineering and providing credit strategy inputs. A successful Analytics Engineer is able to blend business acumen and software engineering best practices while effectively communicating with stakeholders. As an early member of the team, you will also help shape our overall credit data strategy at Wealthsimple.

- Build data models in the cloud data warehouse that will be used as the source of truth for analytics and machine learning

- Apply software engineering best practices like version control and continuous integration to the analytics code base

- Ideate and implement new machine learning model features by contributing to the internal Feature Store

- Translate business requirements into data models that will help stakeholders answer key business questions

- Support end-to-end development of reports/dashboards/tools used by your direct stakeholders and a diverse set of teams across the company

- Ensure data models are well tested, documented and maintained

- 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 your teammates. We value making others successful

- Strong technical skills in manipulating large data sets with complex SQL and Python

- Expertise in data visualization

- Experience with dbt

- Experience with parallel computing frameworks such as Spark or Dask

- Comfortable with software engineering best practices like version control and using Git

- Experience with cloud data warehousing (e.g. Snowflake,Bigquery,Redshift)

- Experience with machine learning feature engineering

- Excellent communicator who is able to translate business requirements into data models and maintain clear documentation

- Able to build and maintain multi-functional relationships with various teams across the business

- Experience with data visualization tools on the cloud (e.g. Periscope Data / Quicksight) is a plus

- Experience working in the credit domain is a plusExperience with graph databases is a plus