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161 Bay Street (93021), Canada, Toronto,Toronto, Ontario, Principal Associate Data Scientist, Machine Learning About Capital One Canada. For 30 years, we’ve been on a mission to change banking for good. We challenge the traditional bank stereotype, fostering a culture where innovation thrives and bold ideas are celebrated. We’re driven by what’s possible, leveraging the power of data and technology to empower innovative solutions, inspire one another to dream boldly, and take transformative ownership of decisions and outcomes that directly impact millions of Canadians. Every challenge is an opportunity to lead from the front, working together toward a shared vision that extends far beyond banking. We balance high-performance with investment in your long-term success, ensuring you have the support you need to do your best work. Here, you’ll take full accountability for your path, upskilling through hands-on experience and mentorship, to turn your curiosity into a career built on your own terms. Are you ready to redefine what’s next?

About the Team At Capital One

When we launched as a startup we disrupted the credit card industry by individually personalizing every credit card offer using statistical modelling 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.

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.

You’ll be empowered to take end-to‑end ownership of your work and your career, backed by a high-performance, hybrid culture and holistic suite of benefits designed to support your whole self.

Take ownership of your own potential: Whether you’re looking to upskill, pivot into new business areas, or master your craft, you’ll have access to tools and mentorship to reach your potential and define your career trajectory.

Find your rhythm: We believe trust fosters the flexibility and autonomy required to balance personal needs with a focus on high performance. We support a hybrid model – with 3 days in the office per week – that gives room for both collaboration and personal commitments.

Benefits built for your life

We take a holistic approach to well‑being, providing support for you and those who are most important to you. This includes:

• full coverage for spouses, domestic partners and dependents
• a one-time Work From Home allowance to build your comfortable workspace
• up to $3,000 in mental health coverage
• up to $5,000 in annual tuition subsidies

You’ll find that Capital One is committed to helping you thrive and evolve every step of the way.

The expected annual salary range for this position is $148,120 to $169,050

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.

Capital One Canada is an equal opportunity employer committed to fostering a diverse and inclusive work environment. We consider all qualified applicants and will meet the needs of those requiring reasonable accommodations.

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 ARCanada@capitalone.com. 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 Careers@capitalone.com

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).

At Capital One, we’re building a leading information-based technology company. Still founder‑led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit.