1750 Tysons (12023), United States of America, McLean, Virginia

Director, Data Science, Fraud Detection

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.

The mission of this role is to drive the continual transformation of Capital One Consumer Bank's Customer Protection Data Science division. As the leading machine learning group, defining the next generation of banking, you will drive innovation that hardens our defenses against various types of bank fraud. In this role, you'll be central to determining our vision and strategy for machine learning applications in fraud detection and prevention that deeply impact the lives and financial freedom of our 12 million consumer bank customers.

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

The Customer Protection Data Science team has a relentless focus on the craft of data sciences spanning statistics, machine learning and distributed computing domains. Our relentless innovation is aimed towards continually identifying fraud attacks across every stage of the customer life cycle. You will be working with cross functional teams including product, engineers and business analysts to identify and enable real-time intelligent decisions as part of our defenses. This is core to delivering the Bank's mission of Changing Banking for Good as it will enable easy access to banking services to all consumers.

In this role, you will:

• Build and deliver a comprehensive machine learning roadmap across bank customer life cycle from account opening to account management that enables customer base growth and faster access to money while preventing fraudulent activity
  
• Partner with senior leaders and partner teams in problem framing and conception of ideas, develop consensus and execute on the machine learning agenda
  
• Lead a data science team and build machine learning models through all phases of development, from design, testing, data gathering, training, evaluation, validation, and implementation
  
• Partner with a cross-functional team of product managers, software engineers, and business analysts to launch machine learning solutions into production
  
• Actively identify and manage model risks in line with model risk management policies
  
• Identify, evaluate, and deploy new algorithms, data strategies, testing strategy, and implementation capabilities to drive continuous innovation
  
• Lead, recruit, and grow a team of data scientists to achieve their professional goals
  

The Ideal Candidate is:

• 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
  
• Achiever. You at ease in a fast pace environment defending against fraud and are driven for action and get things done
  
• Experienced. You've built machine learning models over TB scale data, validated them, back tested them and know what it takes to launch them in a real-time production environment
  
• Team oriented: You excel at partnering with cross functional teams to champion the field of data science achieve collective goals
  
• 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
  

Basic Qualifications:

• Bachelor's Degree plus 9 years of experience in data analytics, or Master's Degree plus 7 years of experience in data analytics, or PhD plus 5 years of experience in data analytics
  
• At least 4 years of experience in open source programming languages for large scale data analysis
  
• At least 4 years of experience with machine learning
  
• At least 4 years of experience with relational databases
  

Preferred Qualifications:

• PhD in Computer Science (Machine Learning, Statistics, Math or equivalent) plus 5 years of experience in data analytics
  
• At least 3 year of experience working with AWS
  
• At least 3 year of experience managing people
  
• At least 5 years of experience in Python, Scala, or R for large scale data analysis
  
• At least 10 years of experience applying machine learning to solve complex problems for large scale applications
  

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.