Powering machine learning-driven product management

Capital One ML program advances product management

At Capital One, whether we’re helping consumers shop more safely online or sharing new insights into their finances, we’re always working to find ways to use technology to make things easier and better for our customers. And customer expectations are evolving — fast — especially in the wake of the pandemic. More and more, customers expect experiences that are intelligent, personalized, and interactive. Our technology transformation journey has ensured that we are well positioned to continue delivering on the innovation that is table stakes for keeping pace in today’s world.

Today, our associates are using data at scale, machine learning, and the power of the cloud to solve unique, challenging technology problems and deliver intelligent solutions that benefit millions of customers — like our award-winning mobile app, our virtual card numbers, and our enhanced abilities to detect fraud, to name a few.

Product Management brings together our collective expertise such as data-driven technology and human-centered design to harness the power of machine learning in some of our most important customer experiences. As we continue to infuse machine learning-based systems, services, and products across Capital One, thousands of our associates will be building, deploying, and managing products with machine learning elements. 

Successfully getting machine learning projects into production requires the collaboration and expertise of a cross functional team — including product management, data science and machine learning, engineering, analytics, risk management, and human-centered design. Each of these areas are critical in their own right, with the product manager as the function that is accountable for defining, tracking, and owning the outcomes of the product, including how machine learning drives it. In essence, today’s top product managers need to understand exactly how, when (and when not) to incorporate machine learning into their products to achieve the best results for their customers.

That’s why we’re excited to launch a new skills development program to equip our product managers with the world-class skills they’ll need to build the machine learning capabilities of the future, called the Product Manager Machine Learning certification. The program will supercharge the skills of our product managers and to help them identify opportunities where AI can make a difference, build and deploy AI by working with data scientists, engineers and designers, and manage the most forward-leaning machine learning capabilities for our customers and associates. 

The program, jointly developed between Capital One and one of our key university partners, offers our Product Managers the ability to learn how to move a machine learning project across the entire lifecycle. It includes academic theory and hands-on learning, with application-oriented use cases both from outside and inside Capital One. Program facilitators and coaches are meant to maximize the learning opportunity for our associates while ensuring a collaborative, supportive community of learners.

The nine-week program includes self-paced learning content from industry experts; internal Capital One case studies and content; weekly learning circles; learning facilitators and Capital One coaches; and a capstone project. Focus areas include: 

  • Intro to ML & AI including identifying and valuing ML opportunities
  • Data topics, needs, opportunities, challenges
  • Traditional ML algorithms
  • Advanced ML algorithms, including Computer Vision & Natural Language Processing
  • Data and ML platforms
  • Deployment, launch/scale strategies, and experimentation
  • Monitoring and MLOps
  • ML Risk Management, Ethics, Responsible AI, and Privacy
  • Case Studies from Capital One, financial services broadly, and other industries

The program will start with approximately 200 associates each year. An incredibly talented group of individuals from Capital One’s Product College — an internal Capital One learning and development space for Product Managers led by product experts — and across the broader company are working to build and manage this program. 

Ultimately, the combination of real-time, intelligent technology and top-flight product management will enable us to continue unlocking new opportunities and delivering exceptional experiences to our customers. This is core to our vision to continually make banking easier and better for consumers – to better understand their needs, goals, and aspirations by delivering truly personalized experiences. And it all relies on the products we’re developing with the human users in mind — from those products used by our associates to those that our customers interact with and rely on everyday.

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Nurtekin Savas, VP, Head of Machine Learning and Data Science, Enterprise Platforms & Products

Nurtekin is the VP and Head of Machine Learning for the Enterprise Products and Platforms organization at Capital One. His main focus is using machine learning to increase data quality through intelligent automation and data labeling, delivering personalized and real time customer experiences, reducing friction from customer journeys and curbing fraud. Prior to Capital One he was the Head of AI for Fidelity Investments’ Personal Investing organization and led the DS and ML teams in Amazon Payment Products. Nurtekin has experience leading many areas in machine learning including personalization, recommender systems, targeting models, NLP, computer vision, content generation, data labeling, active learning, conversational AI, econometrics and model governance/Ethics in ML. Nurtekin is an engineer with graduate degrees in Finance, Business and Data Science. Nurtekin is passionate about education and serves as an advisor to the Boston College Applied Economics program. Nurtekin lives in the Greater Boston area with his wife and two kids.

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