Analytics Engineer - Fraud

Analytics Engineer - Fraud

This job is no longer open
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.

About the team

The Fraud team is responsible for helping Wealthsimple grow, safely. We look to balance fraud risk and customer experience: our mandate is to prevent losses while inserting minimal friction to customers across all products. We employ a multifaceted approach to fraud detection, mitigation and prevention. We build solutions to meet the needs of our customers. Whether that be designing products that are resilient to fraud risk or using predictive modelling to flag suspicious activity, analytical rigour is the underpinning of the decisions that we make.

We are hiring for an Analytics Engineer in the fraud domain to work with data scientists, data analysts and product managers. You will be responsible for building robust, efficient and integrated data models that enable our fraud analytics and machine learning. These data models will serve as the foundation of our fraud analytics strategy, allowing the team to discover fraud trends faster and use data to more accurately target our fraud measures. You will play a critical role in building the source of truth in the data warehouse. A successful Analytics Engineer is able to blend business acumen and software engineering best practices while effectively communicating with stakeholders.

In this role, you will have the opportunity to:

Build data models in the cloud data warehouse that will be used as the source of truth for analytics
Apply software engineering best practices like version control and continuous integration to the analytics code base
Translate business requirements into data models that will help stakeholders answer key business questions
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 their teammates. We value making others successful

Skills we are looking for:

Excellent SQL
Experience with dbt
Comfortable with software engineering best practices like version control and using Git
Experience with a cloud data warehousing (Snowflake, Bigquery, Redshift)
Proficient understanding of data warehousing methodologies and concepts (Kimball, Inmon, etc)
Experience working as part of a data team; either a data analyst, data scientist, or data engineer
Excellent communicator who is able to translate business requirements into data models and maintain clear
Knowledge of another programming language e.g. Python is a plus
Fivetran or Stitch for data extraction and loading as Plus
Experience working in the fraud domain is a plus
This job is no longer open
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