Senior Manager, Data Analysis - Data Management Risk and Analysis

Capital One•McLean, VA

1d•Onsite

About The Position

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 Manager, you will partner cross-functionally with teams throughout the company to validate business impacting analytical tools. You will enhance your technical and analytical skills, while also working with leaders to influence business strategies. With a network of hundreds of Data Analysts, Quants, and Data Scientists, challenging projects with an eye on the bottom line and a focus on work/life balance, we’ve created a dynamic environment with plenty of room for you to learn, grow, and realize your full potential. Specifically in the role, as a Second Line Data Risk advisor, you will be acting as a trusted data risk advisor to divisions (first line business units) and technology partners. You will leverage your deep expertise in data risk management to provide effective challenges, ensuring the company’s data management practices align with both regulatory requirements and enterprise risk appetite. This role is an opportunity to take on key responsibilities in identifying potential data risks, influencing key stakeholders, and assessing data risk across Capital One divisions. As part of the second line of defense, you will engage with product and technology partners, providing insight and influencing the integration of data risk controls into day-to-day operations. You’ll bring a proactive, innovative mindset to designing processes and performing risk assessments to safeguard Capital One's data management environment.

Requirements

Currently has, or is in the process of obtaining a Bachelor’s Degree in quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science or a related quantitative field) plus at least 7 years of experience performing data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus at least 5 years of experience performing data analytics with an expectation that required degree will be obtained on or before the scheduled start date.
At least 5 years of experience performing professional data analysis work
At least 5 years of experience leading and developing with open source data technologies
At least 2 years of experience managing people

Nice To Haves

Master’s Degree or PhD in a Finance, Economics, Statistics, Mathematics, Industrial Engineering, Operations Research, or a related field
At least 7 years of experience in statistical or econometrics hands-on work
At least 5 years of experience manipulating and performing analysis with large data sets
At least 5 years of experience in financial services industry
At least 5 years of experience in developing statistical or econometric models
At least 5 years of experience in validating statistical or econometric models
At least 2 years of experience with data governance
At least 2 years of experience with predictive analytics

Responsibilities

Refining a new Enterprise-wide analytical tools validation framework
Planning and executing validation projects
Assessing the quality and risk of analytical tool methodologies across Capital One, and the nature of tools usage within those processes
Understanding technical issues in analytical tools and assessing tools risks and opportunities
Independently researching, identifying, and prototyping industry best practices for emerging analytical tools
Communicating results clearly and concisely both verbally and through written communications via validation reports and presentations
Leveraging education, colleagues and training opportunities to develop solutions to business problems
Coaching and mentoring junior staff
Build strong relationships with business and technology partners to become a trusted data risk advisor, providing insight into data management risks, guidance on technical control needs to manage data, and shaping risk mitigation strategies across the enterprise.
Perform gap assessments to identify weaknesses in current data management controls/processes, technical designs, architecture data flow diagrams, and propose actionable recommendations to drive organizational transformation and compliance.