161 Bay Street (93021), Canada, Toronto,Toronto, Ontario, Senior Manager, 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.

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 200 company and a leader in the world of data-driven decision-making.

As a Senior Data Science Manager at Capital One, you’ll be 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 unlock the big opportunities that help everyday people save money, time, and agony in their financial lives. Overseeing the development of software to operationalize, clean, and investigate large,



messy data sets of structured and unstructured data Networking with various teams to explore internal and external data sources and APIs to help uncover new trends and improve analysis Designing and contributing to highly scalable data pipelines, machine learning models, tools, and products to enable the analyst community to fully leverage the power of AWS Working with various teams to analyze large swaths of data in order to optimize various business programs Investigating the impact of new technologies on the future of digital banking and the financial world of tomorrow Creative: Big, undefined problems and petabytes of data don’t frighten you. You’re used to working with abstract data, and you love discovering recent narratives in unmined territories.

You know how to deliver through others while paving the way for their growth.

Proactive: You will want to share your knowledge with your peers and contribute back to inner/open source projects which you might consume. At least 7 years of experience in open source programming languages for large scale data analysis (Python, Scala, or Java) At least 7 years of experience with version control systems like Git and GitHub.



At least 7 years of experience with relational databases and programming in SQL At least 2 years of experience with machine learning workflows Bachelor’s Degree or Master’s Degree or PhD in a quantitative field ~ Experience working with AWS (EC2, S3, Lambda, RDS, etc.) ~ 2+ years experience with machine learning workflows ~7+ years experience in Python ~7+ years’ experience with SQL ~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.

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. 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 This role is also eligible to earn performance-based incentive compensation, which may include cash bonus(es). Weembrace 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.

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. #

📌 Head of Machine Learning and Data Science (Toronto)
🏢 Capital One
📍 Toronto