Product Manager (Data) - Business Cards & Payments

Product Manager (Data) - Business Cards & Payments

Product Management at Capital One is a booming, vibrant craft that requires reimagining the status quo, finding value creation opportunities, and driving innovative and sustainable customer experiences through technology. We believe our portfolio of businesses and investments in growth and transformation will result in a company with the scale, brand, capabilities, talent, and values to succeed as the digital revolution transforms our society and our industry.

About the Team
In Business Cards & Payments (BC&P), we are on a mission to pave the path for businesses to do more business. We aspire to be at the heart of our business customer’s financial ecosystem with market leading products, simple & intuitive experiences that bring undeniable value.

As a Data Product Manager on the Business Cards & Payment team, you will take ownership for our existing ML product and its data pipelines. You will work closely with business analysts, engineers, data scientists, product managers, and other cross functional teams to create integrated roadmaps, prioritize development, manage releases, define metrics and key results that will ladder up to customer and business value.

Primary Responsibilities

• The Data Product Manager is responsible for the core ML prediction product and its associated data within our product ecosystem.

• Define the vision for the ML prediction product and its data pipelines that solves customer problems and brings business value. 

• Develop a 12 month+ roadmap (updated quarterly) for the core ML product and socialize with stakeholders for buy-in.

• Lead team(s) of data scientists, software and data engineers to develop and implement ML model improvements, partnering with Enterprise teams where possible. Ensure that the technical architecture supports the evolving needs of current and future use cases.

• Implement best practices in data and ML model pipelines to improve data quality and model accuracy. Ensure compliance with Enterprise data requirements and data patterns.

• Design and implement A/B tests and experiments related to data quality, model performance, and system reliability. Analyze results and identify areas for improvement. Communicate the results of back-end tests and experiments to stakeholders. Partner with analysts, data scientists, designers, engineers, and others to continuously harvest insights from experiments and refine the roadmap.

• Define product requirements, rationalize & recommend sequencing, goal setting, story writing, product execution, testing, and product roll-out strategy. 

• Define and track key performance indicators (KPIs) related to ML model performance, data quality, and system performance. 

• Champion the implementation of robust monitoring and alerting systems to detect and address data quality issues, ML feature or model drift and performance degradation. Partner with other internal teams on data quality standards and enhancements.

• Identify and address technical challenges and roadblocks.

Our Data Product Managers:

• Have a customer-first mindset

• Thrive at the intersection of data and business strategy - able to understand complex business intent and translate strategy into requirements that promote consistent, reusable and interoperable data consumption.

• Framework driven approach to problem solving with ability to simplify technical complexity and drive well-educated business decisions across stakeholders.

• Exceptional cross-team collaboration; able to work across different functions, organizations, and reporting boundaries to get the job done. 

• A strong communicator who can advance initiatives and create consensus through clear, concise, and contextually relevant messaging.

• Highly tuned emotional intelligence, good listener, and deep seated empathy for teams and partners.

• Have product centric mindset to take a product from ideation to production and continually iterate improvements.

• Have working knowledge and passion for emerging technologies to incorporate into building great products. Proficiency in handling large data files using SQL, Python, and/or R.

• Someone who is not afraid to challenge the norm and do what is right for the team.