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Added 9 mins ago
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Founding CTO
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- Full-time
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Added 39 mins ago
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Added 4 hours ago
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Capital One

Director, Data Science

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Posting language: English
Posted: Oct 6, 2026

Original job description

161 Bay Street (93021), Canada, Toronto,Toronto, Ontario,Director, Data Science

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

Data is at the center of everything we do. 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 200 company and a leader in the world of data-driven decision-making.

We're building a portfolio of agentic AI products to transform Capital One's engineering organizations and lines of business – autonomous coding agents, context engineering, and agentic model-development lifecycle to name a few. We're creating a new science team to help define the long-term strategy, analyze & optimize impact throughout the ecosystem, and drive business value at enterprise scale. As a scientist on the team, you'd design AI/ML models and help build the solutions behind these products. You'd also own the science that guides them: designing experiments (A/B tests), modeling telemetry, and turning the results into AI strategy and guidance for C-suite leadership.

About the Role

As a 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 AI and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

In this role, you will:

Partner with a cross-functional team of data scientists, AI & ML engineers, and product managers to deliver enterprise products customers love
Leverage a broad stack of technologies - Python, Conda, AWS, H2O, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
Flex your interpersonal skills to translate the complexity of your work into tangible business goals

The ideal candidate is:

Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
Statistically-minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.

Basic Qualifications:

Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date :
- A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 9 years of experience performing data analytics
- A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 7 years of experience performing data analytics
- A PHD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 4 years of experience performing data analytics
At least 4 years of experience leveraging open source programming languages for large scale data analysis
At least 4 years of experience building/deploying AI/ML models in production
At least 4 years of experience designing and analyzing A/B tests

Preferred Qualifications:

PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics
3+ years of experience working with AWS
5+ years of experience in Python, Scala, or R for large scale data analysis
5+ years of experience with machine learning
5+ years of experience with Spark

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 and 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.

This posting is for an existing vacancy.

This role is 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).

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More about this job

Responsibilities

You will partner with cross-functional teams to build and deploy AI/ML models while defining long-term data science strategy. Additionally, you will design experiments and translate complex technical insights into actionable business goals for leadership.

Requirements

Candidates must hold a quantitative degree (Bachelor's, Master's, or PhD) with several years of relevant experience in data analytics and AI/ML production. Proficiency in open-source programming languages and experience with large-scale data analysis are required.

Skills

Data science
Machine learning
Python
AWS
Spark
Statistical modeling
A/B testing
AI strategy
Data analytics
Deep learning
Clustering
Classification
Sentiment analysis
Time series
Cloud computing
Leadership

Benefits

Health insurance
Work from home allowance
Mental health coverage
Tuition subsidies
Performance-based incentive compensation

Visa sponsorship

Not detected in the job text

Keywords

Data Science
Machine Learning
Artificial Intelligence
Python
AWS
Spark
H2O
Conda
Statistical Modeling
A/B Testing
Big Data
Cloud Computing
Deep Learning
Clustering
Classification
Sentiment Analysis
Time Series
Data Analytics
Agentic AI
Telemetry
Strategy
Leadership
Mentorship
Quantitative Analysis
Operations Research
Mathematics
Computer Science
Economics
Statistics
Production Deployment

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