Principal Associate Data Scientist, Machine Learning
Location: Toronto, ON
Time Type: Full time
Job Description
161 Bay Street (93021), Canada, Toronto,Toronto, Ontario,Principal Associate Data Scientist, Machine LearningAbout Capital One Canada.
For 30 years, we’ve been on a mission to change banking for good and build relationships by making credit accessible, simple, intuitive and rewarding. We want to help Canadians succeed with credit, because we believe in people — in our customers, in our associates, and in talent like you!
About the Team
At Capital One, data is at the center of everything we do. When we launched as a startup we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 100 company and a leader in the world of data-driven decision-making.
About the Role
As a Machine Learning Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in distributed computing technologies and operating across billions and billions of customer transactions to build cutting edge models and unlock the big opportunities that help everyday people save money, time, and agony in their financial lives.
Your Responsibilities:
On any given day, you could be:
Writing software to extract, clean, and investigate large, messy data sets of numerical and textual data
Building, deploying, and maintaining machine learning models (Gradient Boosting Machines, Neural Networks, etc.) from development, validation, through to deployment in production
Developing and optimization model development pipelines that enable rapid experimentation and optimization
Designing and analyzing experiments to optimize business strategies
Investigating the impact of new technologies, data sources, and methodologies in order to remain on the cutting edge of data science.
The Ideal Candidate will be:
Curious: You ask why, you explore, you’re not afraid to share your disruptive ideas. You know Python and are constantly exploring new open source tools, and hitting up AI agents on a regular basis.
A Wrangler: You know how to programmatically extract data from various databases and APIs, bring it through a transformation or two, and leverage it to improve your model’s accuracy.
Creative: Big, undefined problems and petabytes of data don’t frighten you. You’re used to working with abstract data, and you love discovering new narratives in unmined territories.
Proactive: You want to share your knowledge with your peers and contribute back to inner/open source projects which you might consume.
An Expert: You have superpowers you can’t wait to share. You have expertise in key aspects of model development, model deployment, or inference such that you are the go-to person in those areas.
An Emerging Leader: You feel comfortable running point on big, complex projects. You know how to motivate others and bring them along your journey. You can paint a compelling picture of your recommendations and manage the message toward both technical and non-technical audiences.
Basic Qualifications:
At least 3 years of experience in open source programming languages for modeling (Python or R)
At least 3 years of experience with version control system like GitHub
At least 3 years of experience with machine learning or predictive modeling (H2O, XGBoost, TensorFlow, etc...)
At least 3 years of experience with SQL
Preferred Qualifications:
Bachelor’s Degree in a quantitative field or Master’s Degree or PhD
Experience working with AWS (EC2, S3, Lambda, RDS, etc.)
Experience working with advanced Git Workflows (Pull Requests, Code Reviews, Issues, and Branching)
Experience writing unit tests and integrating with CICD tools (Jenkins, CircleCI, etc.)
Experience with experimental design
AI agent power user
At least 5 years’ experience in Python or R
At least 5 years’ experience with machine learning / predictive modeling (H2O, XGBoost, TensorFlow, etc.)
At least 5 years’ experience with SQL
Experience with financial data
Working at Capital One.
Enjoy a hybrid work environment, with 3 days in the office. Build a comfortable workspace with our one-time, Work From Home allowance and enjoy our head office located conveniently across the street from Union Station.
Live well—physically, financially and emotionally. Receive support for you and those who are most important to you, with full coverage for spouses, domestic partners, and dependents. With up to $3000 in mental health coverage and up to $5000 in tuition subsidies per year—and much more—you’ll discover that Capital One is committed to helping you live your best life.
This posting is for an existing vacancy.
The expected annual salary range for this position is $134,400 to $153,300. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es). Incentives could be discretionary or non discretionary depending on the plan.
We embrace the responsible use of artificial intelligence (AI) to enhance the candidate experience and streamline our recruitment processes. However, no hiring decisions are made using AI as every hiring decision is made by our hiring managers, business interviewers, and recruitment professionals. Our teams are equipped with training that empowers them to use AI responsibly.
We may use your information for automated decision making. We may, for certain purposes, render a decision based exclusively on automated processing of your personal information as a part of the candidate screening process.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at [email protected]. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to [email protected]
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
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