At Capital One, we’re changing banking for good. We were founded on the belief that no one should be locked out of the financial system. We’re dedicated to helping foster a world where everyone has an equal opportunity to prosper.  

We’re a bank. But we don’t think like one. We’re always thinking about what’s next. About how we can innovate, inspire, and develop the tools our customers need to improve their financial lives. 

Machine learning is at the heart of our approach. We provide millions of customers with individualized, real-time experiences, protection, and decisions driven by machine learning and advanced analytic capabilities. The Enterprise Tooling team maintains a suite of reusable AI/ML tools that empower Capital One developers to rapidly bring models to market and deliver next-generation customer experiences. 

As a Manager, Product Manager on the Enterprise ML Tooling product team, you will be the voice of the customer, identifying opportunities for reuse, standardization, and innovation. You’ll collaborate with a cross-functional team to define requirements and deliver high value solutions to the enterprise. 

The ideal candidate for this role is passionate about technology and deeply empathizes with customer needs. They are comfortable in conversation with stakeholders ranging from technical customers to senior leadership. 

Specific responsibilities include, but are not limited to:

• Develop and communicate the product vision for key AI/ML capabilities.

• Prioritize the product backlog to maximize business and customer outcomes.

• Incorporate design thinking and analytics to inform product design.

• Enable collaboration and ensure communication between teams.

• Maintain a healthy backlog of work and play a critical role in many agile ceremonies.

• Support the team with escalation and resolution of impediments.

• Serve as the connection between customers, Capital One’s mission, and your team.

We want you if you are:

• Passionate about building impactful products.

• You deeply understand the needs of modern data scientists and machine learning engineers

• You enjoy putting yourself in the shoes of customers. Even better if you have experience doing this with internal customers. 

• You have experience building machine learning models or shipping AI/ML-powered products 

• You are a learner who is able to quickly get up to speed in a highly technical environment.

• You are experienced working in an Agile environment.

• You are a do-er who can also zoom out and think strategically.

• You have excellent oral and written communication skills.

• You are highly collaborative and have the ability to influence and lead.

Basic Qualifications:

• Bachelor’s Degree or military experience

• At least 3 years of experience in product management or at least 3 years of experience in product design, agile delivery, business analysis, data science, or software engineering  

Preferred Qualifications:

• Bachelor’s Degree in Computer Science or Engineering

• MBA or Master’s degree 

• 3+ years of experience in Agile product management

At this time, Capital One will not sponsor a new applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. New York City (Hybrid On-Site): $163,300 - $186,400 for Manager Product Management Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.